Matt leads the software research and advisory for the Analytics and Data expertise at ISG Software Research, covering software that improves the utilization of information across business and IT. His focus areas of coverage include analytics, data intelligence, data operations, data platforms, and streaming and events. Matt’s specialization is in the operational and analytical use of data and use of AI where enterprises can modernize their approaches to accelerate the value realization of technology investments in support of hybrid and multi-cloud architecture. Matt has been an industry analyst for more than a decade and has pioneered the coverage of emerging data platforms including NoSQL and NewSQL databases, data lakes, and cloud-based data processing. He is a graduate of Bournemouth University.
narration area
Executive Summary
Buyers Guide Overview
ISG Research has conducted market research for over two decades across vertical industries, business applications, AI and IT. We have designed the ISG Buyers Guide™ to provide a balanced perspective of software providers and products that is rooted in an understanding of business and IT requirements. Utilization of our research methodology and decades of experience enables our Buyers Guide to be an effective method to assess and select software providers and products. The findings of this research provide a comprehensive approach to rating software providers and rank their ability to meet specific product and customer experience requirements.
ISG Research has designed the Buyers Guide to provide a balanced perspective of software providers and products that is rooted in an understanding of business and IT requirements.
The ISG Buyers Guide for DataOps is the distillation of continuous market and product research. It is an assessment of how well software providers’ offerings address enterprises’ requirements for DataOps software. The Value Index methodology is structured to support a request for information (RFI) for a request for proposal (RFP) process by incorporating all criteria needed to evaluate, select, utilize and maintain relationships with software providers. The ISG Buyers Guide evaluates customer experience and the product experience in its capability and platform.
The structure of the research reflects our understanding that the effective evaluation of software providers and products involves far more than just examining product features, potential revenue or customers generated from a provider’s marketing and sales efforts. It can ensure the best long-term relationship and value achieved from a resource and financial investment We believe it is important to take a comprehensive, research-based approach, since making the wrong choice of DataOps software can raise the total cost of ownership, lower the return on investment and hamper an enterprise’s ability to reach its potential. In addition, this approach can reduce the project’s development and deployment time and eliminate the risk of relying on opinions or historical biases.
ISG Research believes that an objective review of existing and potential new software providers and products is a critical strategy for the adoption and implementation of DataOps software. An enterprise’s review should include a thorough analysis of both what is possible and what is relevant. We urge enterprises to do a thorough job of evaluating DataOps software and offer this Buyers Guide as both the results of our in-depth analysis of these providers and as an evaluation methodology.
How To Use This Buyers Guide
Evaluating Software Providers: The Process
We recommend using the Buyers Guide to assess and evaluate new or existing software providers for your enterprise. The market research can be used as an evaluation framework to assess existing approaches and software providers or establish a formal request for information from providers on products and customer experience and will shorten the cycle time when creating an RFI. The steps listed below provide a process that can facilitate best possible outcomes in the most efficient manner.
- Define the business case and goals.
Define the mission and business case for investment and the expected outcomes from your organizational and technological efforts.
- Specify the business and IT needs.
Defining the business and IT requirements helps identify what specific capabilities are required with respect to people, processes, information and technology.
- Assess the required roles and responsibilities.
Identify the individuals required for success at every level of the enterprise from executives to frontline workers and determine the needs of each.
- Outline the project’s critical path.
What needs to be done, in what order and who will do it? This outline should make clear the prior dependencies at each step of the project plan.
- Ascertain the technology approach.
Determine the business and technology approach that most closely aligns to your enterprise’s requirements.
- Establish software provider evaluation criteria.
Utilize the product experience: capability and platform with support for adaptability, manageability, reliability and usability, and the customer experience in TCO/ROI and Validation.
- Evaluate and select the software provider and products properly.
Apply a weighting the evaluation categories in the evaluation criteria to reflect your enterprise’s priorities to determine the short list of software providers and products. - Establish the business initiative team to start the project.
Identify who will lead the project and the members of the team needed to plan and execute it with timelines, priorities and resources.
Using the ISG Buyers Guide and process provides enterprises a clear, structured approach to making smarter software and business investment decisions. It ensures alignment between strategy, people, processes and technology while reducing risk, saving time and improving outcomes. The ISG approach promotes data-driven decision-making and collaboration, helping choose the right software providers for maximum value and return on investment.
DataOps
As enterprises embracing artificial intelligence move from initial pilots and trial projects through deployment and into production at scale, many are realizing the critical importance of agile and responsive data processes. These processes are often combined with tools and platforms that facilitate data management and processing to improve trust in the data used for AI and business intelligence.
This has led to increased attention on the role of data operations, which ISG Research defines as the application of agile development, DevOps and lean manufacturing by data engineering professionals in support of data production. DataOps encompasses the development, testing, deployment and orchestration of data integration and processing pipelines, along with improved data quality and validity via data monitoring and observability, enabling the creation and consumption of data products.
DataOps has been part of the lexicon of the data market for almost a decade. It takes inspiration from DevOps, which describes a set of tools, practices and a philosophy used to support the continuous delivery of software applications in the face of constant change. Similarly, DataOps describes a set of tools, practices and a philosophy used to support the continuous processing and delivery of data in the face of constant change.
Interest in DataOps is growing. ISG Research asserts that through 2027 more than one-half of enterprises will have adopted agile and collaborative data operations practices to facilitate responsiveness, avoid repetitive tasks, and accelerate AI initiatives. A variety of products, practices and processes enable DataOps, including products that support agile and continuous delivery of data analytics and AI and continuous, measurable improvement.
It is this emphasis on agility, collaboration and automation that in part separates DataOps from traditional approaches to data management, which typically included batch-based, manual and rigid tools and practices. Almost one-half (49%) of participants in ISG’s 2025 Market Lens Data and AI Program Study agree that data operations should be managed separately from other parts of the IT estate.
However, the distinction between DataOps and traditional data management tools is clearer in theory than in practice. In recent years many providers of traditional data management have incorporated capabilities that make products more automated, collaborative and agile. There is no industry-wide consensus on the level of agility, collaboration and automation that must be provided for products to be considered part of the DataOps category.
In seeking to define DataOps, proponents have focused on the practical application of agile development, DevOps and lean manufacturing to the tasks and skills employed by data engineering professionals in support of data analytics development and operations. This definition emphasizes specific capabilities such as continuous delivery of analytic insight, process simplification, code generation, automation to avoid repeated errors and reduced repetitive tasks, the incorporation of stakeholder feedback and advancement and measurable improvement in the efficient generation of insight from data. The practical definition of DataOps provides a set of criteria for agile and collaborative practices that products and services can be measured against.
The practical definition of DataOps provides a set of criteria for agile and collaborative practices that products and services can be measured against.
Based on our interaction with the software provider and user communities, ISG Research has adopted this set of criteria as a core component of our DataOps coverage and the capabilities against which DataOps products are evaluated in this Buyers Guide. Our criteria are focused on the collaboration, automation, acceleration and ecosystem integration capabilities required to ensure the delivery of agile BI and AI data products through the creation and orchestration of data processing pipelines, incorporating improved data reliability and integrity via data monitoring and observability. These are the key criteria we used to assess DataOps products and services as part of this Buyer’s Guide.
This research is comprised of parallel evaluations of products addressing each of the four core areas of functionality: data pipelines, data orchestration, data observability and data products. Additionally, we evaluated all products in all categories in relation to their support for DataOps practices that address collaboration, automation, acceleration and ecosystem integration
The development, testing and deployment of data pipelines is a fundamental accelerator of data-driven strategies, enabling enterprises to extract data generated by operational applications used to run the business and transport it into the analytic data platforms used to analyze operations. ISG Research defines data pipelines as the systems used to transport, process and deliver data produced by operational data platforms and applications into analytic data platforms and applications for consumption. Healthy data pipelines are necessary to ensure data is ingested, processed and loaded in the sequence required to generate BI and AI.
Given the increasing complexity of evolving data sources and requirements, it is essential to automate and coordinate the creation, scheduling and monitoring of data pipelines as part of a DataOps approach to data management. This is the realm of data orchestration, which ISG Research defines as providing the capabilities to automate and accelerate the flow of data to support operational and analytics initiatives and drive business value via capabilities for the monitoring and management of data pipelines and associated workflow.
Maintaining data quality and trust is a perennial data management challenge, often preventing enterprises from operating at the speed of business.
Maintaining data quality and trust is a perennial data management challenge, often preventing enterprises from operating at the speed of business. In addition to automating and coordinating the creation, scheduling and monitoring of data pipelines via data orchestration, it is also critical to monitor the quality and reliability of the data flowing through those data pipelines. This is achieved using data observability, which ISG Research defines as providing the capabilities for monitoring the quality and reliability of data used for analytics and governance projects as well as the reliability and health of the overall data environment. ISG asserts that through 2027, enterprises will prioritize adoption of DataOps products that address combination of data pipeline development, data orchestration and data observability, reducing the complexity and cost of using multiple tools.
The metrics generated by data observability also form a critical component of the development and sharing of data products, providing the information by which data consumers can gauge if a data product meets their requirements in terms of a variety of attributes including validity, uniqueness, timeliness, consistency, completeness and accuracy.
ISG Research defines data products as the outcome of data initiatives developed with product thinking and delivered as reusable assets that can be discovered and consumed by others on a self-service basis, along with associated data contracts and feedback options. Key capabilities for platforms that enable the development of data products include a dedicated interface for the development and classification of data products and data contracts as well as a dedicated interface for the self-service discovery and consumption of data products and data contracts. Data product platforms should also include the ability for consumers of data products to provide feedback, comments and ratings as well as request improvements or new products, and the ability for data owners to monitor data product usage and performance metrics and view and manage requests for data product modifications and the development of new data products.
As always, however, software products are only one aspect of delivering on the promise of DataOps. New approaches to people, processes and information are also required to deliver agile and collaborative development, testing and deployment of data and analytics workloads, as well as data operations. To improve the value generated from analytics and data initiatives, enterprises need to adopt processes and methodologies that support rapid innovation and experimentation, automation, collaboration, measurement and monitoring, and high data quality.
The ISG Buyers Guide™ for DataOps evaluates software providers and products to address data pipeline development, testing and deployment, data pipeline orchestration, data pipeline observability, and data products. Providers with products that address at least three elements—data pipelines, data orchestration, data observability or data products—were deemed to provide a superset of functionality to address DataOps overall.
This research evaluates the following software providers that offer products to address key elements of DataOps as we define it: Alteryx, AWS, Databricks, DataOps.live, IBM, Informatica, K2view, Microsoft, Palantir, Pentaho, Qlik, SAP, Snowflake and Tencent Cloud.
Key Takeaways
DataOps has emerged as a central discipline for enterprises seeking to accelerate AI initiatives and maintain trust in data across complex environments. As organizations pursue agility and automation in data management, DataOps enables continuous delivery of data products and insight at scale. The ISG Buyers Guide™ for DataOps underscores how integrated pipeline development, orchestration and observability capabilities are reshaping enterprise data operations. These solutions help enterprises build a resilient foundation for data-driven innovation.
Software Provider Summary
The ISG Buyers Guide™ for DataOps evaluates software providers offering products that support data pipeline development, orchestration, observability and data product management. The research assessed 14 providers, with Pentaho ranking highest overall, followed by Databricks and Informatica. Providers were evaluated on Product Experience and Customer Experience criteria and this report provides the results for each provider along with strengths and areas for improvement.
Product Experience Insights
Product Experience measures how effectively providers support the complete lifecycle of onboarding, configuration, operation and maintenance of DataOps products. Leaders in this category—Pentaho, Databricks and IBM—demonstrated strength in both capability and platform criteria. The Capability assessment examined more than 245 function points across 20 sections, while the Platform assessment evaluated adaptability, manageability, reliability and usability. Leaders demonstrated robust, scalable architectures and strong integration across business and IT environments.
Customer Experience Value
Customer Experience evaluates provider commitment, viability and customer success across engagement lifecycles. Databricks, Informatica and Alteryx achieved the highest ratings for customer focus, transparency and overall value delivery. Providers that did not perform as well typically lacked clarity in articulating customer commitments or failed to provide sufficient validation of results. These shortcomings often reflected limited visibility into customer programs or inconsistent support structures.
Strategic Recommendations
Enterprises adopting DataOps should prioritize providers with proven automation and orchestration capabilities to ensure agility and responsiveness. Selecting platforms that unify pipeline management, observability and data product development can reduce operational complexity. Enterprises should also assess the provider’s commitment to customer experience to ensure sustained value and measurable ROI. Effective DataOps investments should advance collaboration, trust and innovation across the organization.
The Findings – DataOps
The software providers and products evaluated in the research provide product and customer experiences, but not everything offered is equally valuable to every enterprise or is needed to operate in business processes and use cases. Moreover, the existence of too many capabilities in products may be a negative factor for an enterprise if it introduces unnecessary complexity. Nonetheless, you may decide that a more comprehensive set of capabilities in the product is important, and where they match your enterprise’s requirements.
An effective customer relationship with a software provider is vital to the success of any investment. The overall customer experience and the full lifecycle of engagement play a key role in ensuring satisfaction and long-term success. Providers with dedicated customer leadership, such as chief customer officers, tend to invest more deeply in these relationships and prioritize customer outcomes to TCO and ROI expectations. It is equally important that this commitment to customer success is clearly demonstrated throughout the provider’s website, buying process and customer journey.
Overall Scoring of Software Providers Across Categories
The research finds Pentaho atop the list, followed by Databricks and Informatica. Providers that place in the top three of a category earn the designation of Leader. Databricks has done so in four categories; Informatica and Pentaho in three; IBM in two and Alteryx, DataOps.live and Microsoft in one category.
The overall representation of the research below places the rating of the Product Experience and Customer Experience on the x and y axes, respectively, to provide a visual representation and classification of the software providers. Those providers whose Product Experience have above median weighted performance to the axis in aggregate of the two product categories place farther to the right, while the performance and weighting for the Customer Experience category determines placement on the vertical axis. In short, software providers that place closer to the upper-right on this chart performed better than those closer to the lower-left.
The research categorizes and rates software providers into one of four categories: Assurance, Exemplary, Merit or Innovative. This represents the software providers’ weighted performance in meeting the requirements in product and customer experience.
Exemplary: This rating (upper right) represents those that performed above median in Product and Customer Experience requirements. The providers rated Exemplary are: Alteryx, Databricks, IBM, Informatica, Microsoft and Pentaho.
Innovative: This rating (lower right) represents those that performed above median in Product Experience but not in Customer Experience. The provider rated Innovative is: DataOps.live.
Assurance: This rating (upper left) represents those that performed above median in Customer Experience but not in Product Experience. The providers rated Assurance are: AWS and SAP.
Merit: This rating (lower left) represents those that did not surpass the median in Customer or Product Experience. The providers rated Merit are: K2view, Palantir, Qlik, Snowflake and Tencent Cloud.
We advise enterprises to use this research as a supplement to their own evaluations, recognizing that ratings or rankings do not solely represent the value of a provider nor indicate universal suitability of a set of products.
Product Experience
The process of researching products to address an enterprise’s needs should be comprehensive and evaluate specific capabilities and the underlying platform to the product experience. 
Our evaluation of the Product Experience examines the lifecycle of onboarding, configuration, operations, usage and maintenance. Too often, software providers are not evaluated for the entirety of the product; instead, they are evaluated on market execution and vision of the future.
The research results in Product Experience are ranked at 80%, or four-fifths, using the underlying weighted performance. Importance was placed on the categories as follows: Capability (30%) and Platform (50%). Pentaho, Databricks and IBM were designated Product Experience Leaders.
Customer Experience
The importance of a customer relationship with a software provider is essential to the actual success of the products and technology. The evaluation of the Customer Experience and the entire lifecycle an enterprise has with its software provider is critical for ensuring satisfaction in working with that provider. The ISG Buyers Guide examines a software provider’s customer commitment, viability, customer success, sales and onboarding, product roadmap and services with partners and support. The customer experience category also investigates the TCO/ROI and how well a software provider demonstrates the product’s overall value, cost and benefits, including the tools and resources to evaluate these factors.
The research results in Customer Experience are ranked at 20%, or one-fifth of the 100% index, an
d represent the underlying provider validation and TCO/ROI requirements as they relate to the framework of commitment and value to the software provider-customer relationship.
The software providers that evaluated the highest in the Customer Experience category are Databricks, Informatica and Alteryx. These category leaders best communicate commitment and dedication to customer needs.
Software providers that did not perform well in this category were unable to provide or make sufficient information readily available to demonstrate success or articulate their commitment to customer experience. The use of a software provider requires continuous investment, so a holistic evaluation must include examination of how they support their customer experience.
Software Provider Inclusion – DataOps
For inclusion in the 2025 ISG Buyers Guide™ for DataOps, a software provider must be in good standing financially and ethically, have at least $10 million in annual or projected revenue verified using independent sources, sell products and provide support on at least two continents, and have at least 50 employees. The principal source of the relevant business unit’s revenue must be software-related, and there must have been at least one major software release in the last 12 months.
Data Operations (DataOps) focuses on the application of agile development, DevOps and lean manufacturing by data engineering professionals in support of data production. DataOps encompasses the development, testing, deployment and orchestration of data integration and processing pipelines, along with improved data quality and validity via data monitoring and observability, enabling the development and consumption of data products.
To be included in the Data Operations Buyers Guide, the product(s) must be marketed as a data operations platform or address the following functional areas, which are mapped into Buyers Guide capability criteria:
- DataOps
- Collaboration
- Acceleration
- Automation
- Ecosystem integration
- At least three of
- Data pipelines
- Data orchestration
- Data observability
- Data products
The research is designed to be independent of the specifics of software provider packaging and pricing. To represent the real-world environment in which businesses operate, we include providers that offer suites or packages of products that may include relevant individual modules or applications. If a software provider is actively marketing, selling and developing a product for the general market and it is reflected on the provider’s website that the product is within the scope of the research, that provider is automatically evaluated for inclusion.
All software providers that offer relevant products and meet the inclusion requirements were invited to participate in the evaluation process at no cost to them.
Software providers that meet our inclusion criteria but did not completely participate in our Buyers Guide were assessed solely on publicly available information. As this could have a significant impact on classification and ratings, we recommend additional scrutiny when evaluating those providers.
Products Evaluated
| Provider | Product Names | Version | Release Month/Year |
|---|---|---|---|
| Alteryx |
Alteryx One Alteryx Connect |
NA v. 2025.1 |
September 2025 May 2025 |
| AWS | Amazon SageMaker | NA | August 2025 |
| Databricks | Databricks Data Intelligence Platform | NA | September 2025 |
| DataOps.live | DataOps.live | NA | September 2025 |
| IBM | IBM watsonx.data integration | NA | September 2025 |
| Informatica | Informatica Intelligent Data Management Cloud | NA | August 2025 |
| K2view | K2view Data Product Platform | v. 8.3.0 | August 2025 |
| Microsoft |
Microsoft Fabric Microsoft Purview |
NA |
August 2025 September 2025 |
| Palantir | Palantir Foundry | NA | September 2025 |
| Pentaho |
Pentaho Data Integration Pentaho Data Quality Pentaho Data Catalog |
v. 10.2 NA v. 10.2.8 |
September 2025 September 2025 September 2025 |
| Qlik | Qlik Talend Cloud | NA | September 2025 |
| SAP | SAP Business Data Cloud | NA | September 2025 |
| Snowflake | Snowflake Platform | NA | September 2025 |
| Tencent Cloud | Tencent Cloud WeData | NA | November 2024 |
Providers of Promise
We did not include software providers that, as a result of our research and analysis, did not satisfy the criteria for inclusion in this Buyers Guide. These are listed below as “Providers of Promise.”
| Provider | Product | Annual Revenue >$10M | Operates on 2 Continents | At Least 50 Employees | Product GA |
|---|---|---|---|---|---|
| Ascend | Ascend | No | Yes | No | Yes |
| Datafold | Datafold | No | Yes | No | Yes |
| Keboola | Keboola | No | Yes | Yes | Yes |
| Nexla | Nexla | Yes | Yes | No | Yes |
| Saturam | Qualdo, Piperr | No | Yes | Yes | Yes |
Data Orchestration
While data-driven enterprises stand to gain a competitive advantage by responding faster to worker and customer demands for more innovative, data-rich applications and personalized experiences, this increasingly relies on a complex array of data pipelines to support agile, continuous data processing. Given the increasing complexity of data pipelines required to support the automation of complex business processes through agentic artificial intelligence, it is essential to coordinate the creation, scheduling and monitoring of data pipelines as part of a DataOps approach to data management.
Data orchestration modernizes traditional data management by automating how data is collected, transformed and activated across distributed environments.
This is the realm of data orchestration, which ISG Research defines as providing the capabilities to automate and accelerate the flow of data across the organization via capabilities for pipeline monitoring, pipeline management and workflow management to support operational and analytics initiatives and drive business.
Data orchestration modernizes traditional data management by automating how data is collected, transformed and activated across distributed environments. It replaces rigid, batch-based processes with agile workflows that enable real-time analytics and decision-making across multiple clouds and systems. Tools like Apache Airflow, Flyte and Metaflow—originating from digital-native innovators—have brought orchestration mainstream, helping enterprises coordinate, monitor and optimize data workflows. As data becomes more fragmented and real-time, orchestration serves as the backbone for efficient, responsive data movement and supports the growing emphasis on data literacy and democratization.
Now central to DataOps ecosystems, orchestration unifies pipeline management, observability and workflow automation to reduce complexity and enhance agility. It also powers AI and ML operations by automating data flows between models, applications and repositories. Though still early in adoption, orchestration is emerging as a cornerstone of enterprise data modernization, enabling faster insights, better collaboration and greater trust in data quality.
The ISG Buyers Guide™ for Data Orchestration evaluates software providers and products in key areas, including data pipeline management, workflow management and pipeline deployment. This research evaluates the following software providers that offer products to address key elements of data orchestration as we define it: Alteryx, Astronomer, AWS, BMC, Boomi, Cloudera, Databricks, DataKitchen, DataOps.live, dbt Labs, Gathr, Google Cloud, IBM, Informatica, K2View, Matillion, Microsoft, Palantir, Qlik, Saagie, SAP, Snowflake, Stonebranch, Tencent Cloud, Workato and Zoho.
Key Takeaways
Data orchestration has become foundational to DataOps and enterprise data modernization. As organizations move toward real-time analytics, AI and continuous data processing, orchestration automates and coordinates complex data flows across systems and environments. This Buyers Guide highlights how orchestration platforms unify pipeline management, observability and workflow automation to reduce complexity and improve agility. Enterprises are increasingly relying on orchestration to accelerate insights and strengthen trust in data quality.
Software Provider Summary
The ISG Buyers Guide™ for Data Orchestration evaluates software providers offering products that support data pipeline management, workflow management and pipeline monitoring. The research assessed 26 providers, with Databricks ranking highest overall, followed by Alteryx and Boomi. Providers were evaluated on Product Experience and Customer Experience criteria and this report provides the results for each provider along with strengths and areas for improvement.
Product Experience Insights
ISG’s Product Experience evaluation, weighted at 80 percent of the overall score, focused on Capability and Platform performance. Databricks, Pentaho and Alteryx emerged as Product Experience Leaders, supported by strengths in functionality breadth and operational maturity. The Capability category emphasized data pipeline management, workflow automation and monitoring, while Platform assessment centered on adaptability, manageability, reliability and usability. Leaders demonstrated robust architectures and intuitive platforms that support secure, scalable and enterprise-grade orchestration.
Customer Experience Value
Customer Experience, weighted at 20 percent of the overall index, evaluated providers’ customer commitment, viability, onboarding, services and value realization. Databricks, Informatica, Alteryx and Boomi achieved the highest results, reflecting mature engagement models and strong ROI communication. Vendors that performed lower often lacked transparency or accessible evidence of customer success and value. Non-Leader providers were challenged by inconsistent support experiences and limited demonstration of customer commitment across lifecycle stages.
Strategic Recommendations
Enterprises should evaluate data orchestration platforms through both capability depth and ecosystem fit, prioritizing secure, flexible and scalable architectures that align with DataOps principles. Given the growing importance of automation and observability, organizations should favor solutions that unify data workflow visibility across hybrid and multicloud environments. Vendors demonstrating clear customer leadership and measurable value delivery will better support long-term data modernization goals. A coordinated orchestration strategy is essential to sustaining agility and governance in enterprise-wide data operations.
The Findings – Data Orchestration
The software providers and products evaluated in the research provide product and customer experiences, but not everything offered is equally valuable to every enterprise or is needed to operate in business processes and use cases. Moreover, the existence of too many capabilities in products may be a negative factor for an enterprise if it introduces unnecessary complexity. Nonetheless, you may decide that a more comprehensive set of capabilities in the product is important, and where they match your enterprise’s requirements.
An effective customer relationship with a software provider is vital to the success of any investment. The overall customer experience and the full lifecycle of engagement play a key role in ensuring satisfaction and long-term success. Providers with dedicated customer leadership, such as chief customer officers, tend to invest more deeply in these relationships and prioritize customer outcomes to TCO and ROI expectations. It is equally important that this commitment to customer success is clearly demonstrated throughout the provider’s website, buying process and customer journey.
Overall Scoring of Software Providers Across Categories
The research finds Databricks atop the list, followed by Alteryx and Boomi. Providers that place in the top three of a category earn the designation of Leader. Databricks has done so in five categories; Alteryx in three; Informatica and Pentaho in two and Boomi, DataOps.live and Microsoft in one category.
The overall representation of the research below places the rating of the Product Experience and Customer Experience on the x and y axes, respectively, to provide a visual representation and classification of the software providers. Those providers whose Product Experience have above median weighted performance to the axis in aggregate of the two product categories place farther to the right, while the performance and weighting for the Customer Experience category determines placement on the vertical axis. In short, software providers that place closer to the upper-right on this chart performed better than those closer to the lower-left.
The research categorizes and rates software providers into one of four categories: Assurance, Exemplary, Merit or Innovative. This represents the software providers’ weighted performance in meeting the requirements in product and customer experience.
Exemplary: This rating (upper right) represents those that performed above median in Product and Customer Experience requirements. The providers rated Exemplary are: Alteryx, AWS, BMC, Boomi, Databricks, Google Cloud, IBM, Informatica, Matillion, Microsoft and Pentaho.
Innovative: This rating (lower right) represents those that performed above median in Product Experience but not in Customer Experience. The providers rated Innovative are: DataOps.live and Stonebranch.
Assurance: This rating (upper left) represents those that performed above median in Customer Experience but not in Product Experience. The providers rated Assurance are: Cloudera and SAP.
Merit: This rating (lower left) represents those that did not surpass the median in Customer or Product Experience. The providers rated Merit are: Astronomer, dbt Labs, Gathr.ai, K2view, Palantir, Qlik, Saagie, Snowflake, Tencent Cloud, Workato and Zoho.
We advise enterprises to use this research as a supplement to their own evaluations, recognizing that ratings or rankings do not solely represent the value of a provider nor indicate universal suitability of a set of products.
Product Experience
The process of researching products to address an enterprise’s needs should be comprehensive and evaluate specific capabilities and the underlying platform to the product experience. Our evaluation of the Product Experience examines the lifecycle of onboarding, configuration, operations, usage and maintenance. Too often, software providers are not evaluated for the entirety of the product; instead, they are evaluated on market execution and vision of the future.
The research results in Product Experience are ranked at 80%, or four-fifths, of the overall rating using the specific underlying weighted category performance. Importance was placed on the categories as follows: Capability (40%) and Platform (40%).
Databricks, Pentaho and Alteryx were designated Product Experience Leaders. While not a Leader, Boomi was also found to meet a broad range of enterprise product experience requirements.
Customer Experience
The importance of a customer relationship with a software provider is essential to the actual success of the products and technology. The evaluation of the Customer Experience and the entire lifecycle an enterprise has with its software provider is critical for ensuring satisfaction in working with that provider. The ISG Buyers Guide examines a software provider’s customer commitment, viability, customer success, sales and onboarding, product roadmap and services with partners and support. The customer experience category also investigates the TCO/ROI and how well a software provider demonstrates the product’s overall value, cost and benefits, including the tools and resources to evaluate these factors.
The research results in Customer Experience are ranked at 20%, or one-fifth of the 100% index, and represent the underlying provider validation and TCO/ROI requirements as they relate to the framework of commitment and value to the software provider-customer relationship.
The software providers that evaluated the highest in the Customer Experience category are Databricks, Informatica, Alteryx and Boomi. These category leaders best communicate commitment and dedication to customer needs.
Software providers that did not perform well in this category were unable to provide or make sufficient information readily available to demonstrate success or articulate their commitment to customer experience. The use of a software provider requires continuous investment, so a holistic evaluation must include examination of how they support their customer experience.
Software Provider Inclusion – Data Orchestration
For inclusion in the 2025 ISG Buyers Guide™ for Data Orchestration, a software provider must be in good standing financially and ethically, have at least $10 million in annual or projected revenue verified using independent sources, sell products and provide support on at least two continents, and have at least 50 employees. The principal source of the relevant business unit’s revenue must be software-related, and there must have been at least one major software release in the last 12 months.
Data orchestration enables the flow of data across the organization via capabilities for pipeline monitoring, pipeline management and workflow management. Given the increasing complexity of evolving data sources and requirements, it’s essential to automate and coordinate the creation, scheduling and monitoring of data pipelines.
To be included in the Data Orchestration Buyers Guide, the product(s) must be marketed as a data orchestration platform or address the following functional areas, which are mapped into Buyers Guide capability criteria:
- DataOps
- Collaboration
- Acceleration
- Automation
- Ecosystem integration
- Data pipeline management
- Data workflow management
- Data pipeline monitoring
The research is designed to be independent of the specifics of software provider packaging and pricing. To represent the real-world environment in which businesses operate, we include providers that offer suites or packages of products that may include relevant individual modules or applications. If a software provider is actively marketing, selling and developing a product for the general market and it is reflected on the provider’s website that the product is within the scope of the research, that provider is automatically evaluated for inclusion.
All software providers that offer relevant products and meet the inclusion requirements were invited to participate in the evaluation process at no cost to them.
Software providers that meet our inclusion criteria but did not completely participate in our Buyers Guide were assessed solely on publicly available information. As this could have a significant impact on classification and ratings, we recommend additional scrutiny when evaluating those providers.
Products Evaluated
| Provider | Product Names | Version | Release Month/Year |
|---|---|---|---|
| Alteryx | Alteryx One | NA | September 2025 |
| Astronomer | Astro | NA | August 2025 |
| AWS | Amazon SageMaker | NA | August 2025 |
| BMC | BMC Control-M | v. 9.0.22 | August 2025 |
| Boomi | Boomi Enterprise Platform | NA | August 2025 |
| Cloudera | Cloudera Data Engineering | v. 1.24.1-H1 | July 2025 |
| Databricks | Databricks Data Intelligence Platform | NA | September 2025 |
| DataOps.live | DataOps.live | NA | September 2025 |
| dbt Labs | dbt | NA | August 2025 |
| Gathr.ai | Gathr | v. 7.5.0 | September 2025 |
| Google Cloud | Google Cloud Composer | NA | September 2025 |
| IBM | IBM watsonx.data integration | NA | September 2025 |
| Informatica | Informatica Intelligent Data Management Cloud | NA | August 2025 |
| K2view | K2view Data Product Platform | v. 8.3.0 | August 2025 |
| Matillion | Matillion Data Productivity Cloud | NA | September 2025 |
| Microsoft | Microsoft Fabric | NA | August 2025 |
| Palantir | Palantir Foundry | NA | September 2025 |
| Pentaho | Pentaho Data Integration | v. 10.2 | September 2025 |
| Qlik | Qlik Talend Cloud | NA | September 2025 |
| Saagie | Saagie | v. 2025.02 | June 2025 |
| SAP | SAP Business Data Cloud | NA | September 2025 |
| Snowflake | Snowflake Platform | NA | September 2025 |
| Stonebranch | Universal Automation Center | v. 7.8.0.0 | August 2025 |
| Tencent Cloud | Tencent Cloud WeData | NA | November 2024 |
| Workato | Workato | NA | September 2025 |
| Zoho | Zoho DataPrep | v.2.0 | July 2025 |
Providers of Promise
We did not include software providers that, as a result of our research and analysis, did not satisfy the criteria for inclusion in this Buyers Guide. These are listed below as “Providers of Promise.”
| Provider | Product | Annual Revenue >$10M | Operates on 2 Continents | At Least 50 Employees | Product GA |
|---|---|---|---|---|---|
| Ascend | Ascend | No | Yes | No | Yes |
| Dagster Labs | Dagster+ | No | Yes | No | Yes |
| Datacoves | Datacoves | No | Yes | No | Yes |
| Datafold | Datafold | No | Yes | No | Yes |
| Keboola | Keboola | No | Yes | Yes | Yes |
| Nexla | Nexla | Yes | Yes | No | Yes |
| Prefect | PrefectCloud | No | Yes | No | Yes |
| Promethium | Promethium | No | Yes | No | Yes |
| PurpleCube AI | PurpleCube AI | No | Yes | No | Yes |
| Saturam | Piperr | No | Yes | Yes | Yes |
Data Pipelines
The development, testing and deployment of data pipelines is a fundamental accelerator of data-driven strategies. The pipelines enable enterprises to extract data generated by operational applications that run the business and deliver it into the analytic data platforms used to analyze the business.
ISG Research defines data pipelines as the systems used to transport, process and deliver data produced by operational data platforms and applications into analytic data platforms and applications for consumption. Healthy data pipelines are necessary to ensure data is ingested, processed and loaded in the sequence required to generate business intelligence and artificial intelligence (AI).
Data pipelines, long central to data management, are now critical to modern enterprises that depend on continuous, data-driven decision-making.
Data pipelines, long central to data management, are now critical to modern enterprises that depend on continuous, data-driven decision-making. They facilitate the flow of data across systems—extracting, transforming, and loading it for analysis—and are increasingly automated through orchestration tools that manage complex workflows. As organizations confront data silos and fragmentation, agile and well-orchestrated pipelines, often integrated with DataOps and observability platforms, have become essential. These systems not only automate development, testing, and deployment but also monitor data quality and pipeline health, reducing operational complexity and enabling trusted, enterprise-wide data access.
Evolving data processing needs are driving the shift from traditional batch ETL to more flexible ELT, zero-ETL and change data capture (CDC) approaches. ELT pushes transformations to the target platform for greater adaptability, while zero-ETL enables near real-time analytics by minimizing preprocessing. CDC further enhances agility by synchronizing incremental data changes instead of entire datasets. Together, these methods—supported by automation, orchestration and emerging AI capabilities—are transforming data pipelines into intelligent, self-optimizing systems. Generative AI, in particular, shows promise for automating pipeline creation, documentation, and integration with AI-driven business processes, signaling the next stage of acceleration in data operations.
The ISG Buyers Guide™ for Data Pipelines evaluates software providers and products in key areas, including data pipeline development, data pipeline testing, and data pipeline deployment. This research evaluates the following software providers that offer products to address key elements of data pipelines as meet our definition: Airbyte, Alteryx, Astronomer, AWS, BMC, Boomi, Databricks, DataKitchen, DataOps.live, dbt Labs, Fivetran, Gathr, Google Cloud, IBM, Informatica, K2view, Kleene, Matillion, Microsoft, Palantir, Qlik, SAP, Snowflake, Tencent Cloud, Workato and Zoho.
Key Takeaways
Enterprises depend on well-orchestrated data pipelines to connect operational and analytic systems, ensuring the continuous flow of trusted data that powers business intelligence and AI. Modern pipelines have evolved beyond traditional batch processing to support real-time and event-driven models using ELT, zero-ETL and change data capture. These approaches improve agility and scalability while reducing complexity. As automation and AI become embedded across orchestration, monitoring and optimization, data pipelines are emerging as intelligent systems that sustain enterprise-wide data operations.
Software Provider Summary
The ISG Buyers Guide™ for Data Pipelines evaluates software providers offering products that support data pipeline development, testing and deployment. The research assessed 26 providers, with Databricks ranking highest overall, followed by Informatica and IBM. Providers were evaluated on Product Experience and Customer Experience criteria and this report provides the results for each provider along with strengths and areas for improvement.
Product Experience Insights
ISG Research weighted Product Experience at 80 percent of the overall rating, emphasizing Capability and Platform as core factors. Databricks, IBM, Pentaho and Informatica were designated Product Experience Leaders. Databricks, Informatica and Microsoft led in Platform for delivering adaptable, reliable and user-friendly foundations, while DataOps.live, Databricks and Pentaho led in Capability for broad functional coverage. Leaders demonstrated robust integration, governance and usability across complex enterprise environments.
Customer Experience Value
Customer Experience accounted for 20 percent of the evaluation, measuring provider commitment, viability and total cost of ownership. Databricks, Informatica, Alteryx and Boomi achieved the highest scores, supported by clear communication of customer value and strong success enablement. Non-Leader providers struggled to make customer success information accessible or lacked evidence of measurable ROI, with challenges most apparent in service transparency and partner engagement.
Strategic Recommendations
Enterprises should select data pipeline platforms that balance automation, governance and flexibility to scale across hybrid and multicloud environments. Integrating pipeline orchestration with DataOps and observability tools enhances data trust and system reliability. Organizations modernizing from ETL to ELT or CDC should prioritize products that minimize latency while maintaining governance controls. Investing in providers that combine platform maturity with demonstrated customer success will deliver long-term adaptability and measurable business outcomes.
The Findings – Data Pipelines
The software providers and products evaluated in the research provide product and customer experiences, but not everything offered is equally valuable to every enterprise or is needed to operate in business processes and use cases. Moreover, the existence of too many capabilities in products may be a negative factor for an enterprise if it introduces unnecessary complexity. Nonetheless, you may decide that a more comprehensive set of capabilities in the product is important, and where they match your enterprise’s requirements.
An effective customer relationship with a software provider is vital to the success of any investment. The overall customer experience and the full lifecycle of engagement play a key role in ensuring satisfaction and long-term success. Providers with dedicated customer leadership, such as chief customer officers, tend to invest more deeply in these relationships and prioritize customer outcomes to TCO and ROI expectations. It is equally important that this commitment to customer success is clearly demonstrated throughout the provider’s website, buying process and customer journey.
Overall Scoring of Software Providers Across Categories
The research finds Databricks atop the list, followed by Informatica and IBM. Providers that place in the top three of a category earn the designation of Leader. Databricks has done so in five categories; Informatica in three; IBM and Pentaho in two; and Alteryx, DataOps.live, and Microsoft in one category.
The overall representation of the research below places the rating of the Product Experience and Customer Experience on the x and y axes, respectively, to provide a visual representation and classification of the software providers. Those providers whose Product Experience have above median weighted performance to the axis in aggregate of the two product categories place farther to the right, while the performance and weighting for the Customer Experience category determines placement on the vertical axis. In short, software providers that place closer to the upper-right on this chart performed better than those closer to the lower-left.
The research categorizes and rates software providers into one of four categories: Assurance, Exemplary, Merit or Innovative. This represents the software providers’ weighted performance in meeting the requirements in product and customer experience.
Exemplary: This rating (upper right) represents those that performed above median in Product and Customer Experience requirements. The providers rated Exemplary are: Alteryx, Boomi, Databricks, DataOps.live, Google Cloud, IBM, Informatica, Matillion, Microsoft, Pentaho and SAP.
Innovative: This rating (lower right) represents those that performed above median in Product Experience but not in Customer Experience. The providers rated Innovative are: dbt Labs and Palantir.
Assurance: This rating (upper left) represents those that performed above median in Customer Experience but not in Product Experience. The providers rated Assurance are: AWS, BMC, Qlik and Workato.
Merit: This rating (lower left) represents those that did not surpass the median in Customer or Product Experience. The providers rated Merit are: Airbyte, Astronomer, Fivetran, Gathr.ai, K2view, Kleene, Snowflake, Tencent Cloud and Zoho.
We advise enterprises to use this research as a supplement to their own evaluations, recognizing that ratings or rankings do not solely represent the value of a provider nor indicate universal suitability of a set of products.
Product Experience
The process of researching products to address an enterprise’s needs should be comprehensive and evaluate specific capabilities and the underlying platform to the product experience. Our evaluation of the Product Experience examines the lifecycle of onboarding, configuration, operations, usage and maintenance. Too often, software providers are not evaluated for the entirety of the product; instead, they are evaluated on market execution and vision of the future.
The research results in Product Experience are ranked at 80%, or four-fifths, of the overall rating using the specific underlying weighted category performance. Importance was placed on the categories as follows: Capability (40%) and Platform (40%). Databricks, IBM, Pentaho and Informatica were designated Product Experience Leaders.
Customer Experience
The importance of a customer relationship with a software provider is essential to the actual success of the products and technology. The evaluation of the Customer Experience and the entire lifecycle an enterprise has with its software provider is critical for ensuring satisfaction in working with that provider. The ISG Buyers Guide examines a software provider’s customer commitment, viability, customer success, sales and onboarding, product roadmap and services with partners and support. The customer experience category also investigates the TCO/ROI and how well a software provider demonstrates the product’s overall value, cost and benefits, including the tools and resources to evaluate thes
e factors.
The research results in Customer Experience are ranked at 20%, or one-fifth of the 100% index, and represent the underlying provider validation and TCO/ROI requirements as they relate to the framework of commitment and value to the software provider-customer relationship.
The software providers that evaluated the highest in the Customer Experience category are Databricks, Informatica, Alteryx and Boomi. These category leaders best communicate commitment and dedication to customer needs.
Software providers that did not perform well in this category were unable to provide or make sufficient information readily available to demonstrate success or articulate their commitment to customer experience. The use of a software provider requires continuous investment, so a holistic evaluation must include examination of how they support their customer experience.
Software Provider Inclusion – Data Pipelines
For inclusion in the 2025 ISG Buyers Guide™ for Data Pipelines, a software provider must be in good standing financially and ethically, have at least $10 million in annual or projected revenue verified using independent sources, sell products and provide support on at least two continents, and have at least 50 employees. The principal source of the relevant business unit’s revenue must be software-related, and there must have been at least one major software release in the last 12 months.
The development, testing and deployment of data pipelines enables enterprises to extract data from the operational applications and data platforms designed to run the business and load, integrate and transform it into the analytic data platforms and tools used to analyze the business. Data pipelines are a fundamental accelerator of data-driven strategies, and today’s analytics environments require agile data pipelines that can traverse multiple data-processing locations and evolve with business needs.
To be included in the Data Pipelines Buyers Guide, the product(s) must be marketed as a data pipelines platform or address the following functional areas, which are mapped into Buyers Guide capability criteria:
- DataOps
- Collaboration
- Acceleration
- Automation
- Ecosystem integration
- Data pipeline development
- Data pipeline testing
- Data pipeline deployment
The research is designed to be independent of the specifics of software provider packaging and pricing. To represent the real-world environment in which businesses operate, we include providers that offer suites or packages of products that may include relevant individual modules or applications. If a software provider is actively marketing, selling and developing a product for the general market and it is reflected on the provider’s website that the product is within the scope of the research, that provider is automatically evaluated for inclusion.
All software providers that offer relevant products and meet the inclusion requirements were invited to participate in the evaluation process at no cost to them.
Software providers that meet our inclusion criteria but did not completely participate in our Buyers Guide were assessed solely on publicly available information. As this could have a significant impact on classification and ratings, we recommend additional scrutiny when evaluating those providers.
Products Evaluated
| Provider | Product Names | Version | Release Month/Year |
|---|---|---|---|
| Airbyte | Airbyte | v. 1.8 | August 2025 |
| Alteryx | Alteryx One | NA | September 2025 |
| Astronomer | Astro | NA | August 2025 |
| AWS | Amazon SageMaker | NA | August 2025 |
| BMC | BMC Control-M | v. 9.0.22 | August 2025 |
| Boomi | Boomi Enterprise Platform | NA | August 2025 |
| Databricks | Databricks Data Intelligence Platform | NA | September 2025 |
| DataOps.live | DataOps.live | NA | September 2025 |
| dbt Labs | Dbt | NA | August 2025 |
| Fivetran | Fivetran | NA | September 2025 |
| Gathr.ai | Gathr | 7.5.0 | September 2025 |
| Google Cloud | Google Cloud Composer | NA | September 2025 |
| IBM | IBM watsonx.data integration | NA | September 2025 |
| Informatica | Informatica Intelligent Data Management Cloud | NA | August 2025 |
| K2view | K2view Data Product Platform | v. 8.3.0 | August 2025 |
| Kleene | Kleene | NA | September 2025 |
| Matillion | Matillion Data Productivity Cloud | NA | September 2025 |
| Microsoft | Microsoft Fabric | NA | August 2025 |
| Palantir | Palantir Foundry | NA | September 2025 |
| Pentaho | Pentaho Data Integration | v. 10.2 | September 2025 |
| Qlik | Qlik Talend Cloud | NA | September 2025 |
| SAP | SAP Business Data Cloud | NA | September 2025 |
| Snowflake | Snowflake Platform | NA | September 2025 |
| Tencent Cloud | Tencent Cloud WeData | NA | November 2024 |
| Workato | Workato | NA | September 2025 |
| Zoho | Zoho DataPrep | v. 2.0 | July 2025 |
Providers of Promise
We did not include software providers that, as a result of our research and analysis, did not satisfy the criteria for inclusion in this Buyers Guide. These are listed below as “Providers of Promise.”
| Provider | Product | Annual Revenue >$10M | Operates on 2 Continents | At Least 50 Employees | Product GA |
|---|---|---|---|---|---|
| Arch Data | Meltano | No | Yes | No | Yes |
| Ascend | Ascend | No | Yes | No | Yes |
| Dagster Labs | Dagster+ | No | Yes | No | Yes |
| Datacoves | Datacoves | No | Yes | No | Yes |
| Datafold | Datafold | No | Yes | No | Yes |
| FirstEigen | DataBuck | No | Yes | No | Yes |
| Integrate.io | Integrate.io | No | Yes | Yes | Yes |
| Keboola | Keboola | No | Yes | Yes | Yes |
| Mage Technologies | Mage | No | Yes | No | Yes |
| Mozart Data | Mozart Data | No | Yes | No | Yes |
| Nexla | Nexla | Yes | Yes | No | Yes |
| Pipedream | Pipedream | No | Yes | No | Yes |
| Prefect | PrefectCloud | No | Yes | No | Yes |
| Promethium | Promethium | No | Yes | No | Yes |
| PurpleCube AI | PurpleCube AI | No | Yes | No | Yes |
| Saturam | Piperr | No | Yes | Yes | Yes |
| Switchboard Software | Data Automation | No | Yes | No | Yes |
| Torana | iceDQ | No | Yes | No | Yes |
Executive Summary
Buyers Guide Overview
ISG Research has conducted market research for over two decades across vertical industries, business applications, AI and IT. We have designed the ISG Buyers Guide™ to provide a balanced perspective of software providers and products that is rooted in an understanding of business and IT requirements. Utilization of our research methodology and decades of experience enables our Buyers Guide to be an effective method to assess and select software providers and products. The findings of this research provide a comprehensive approach to rating software providers and rank their ability to meet specific product and customer experience requirements.
ISG Research has designed the Buyers Guide to provide a balanced perspective of software providers and products that is rooted in an understanding of business and IT requirements.
The ISG Buyers Guide for DataOps is the distillation of continuous market and product research. It is an assessment of how well software providers’ offerings address enterprises’ requirements for DataOps software. The Value Index methodology is structured to support a request for information (RFI) for a request for proposal (RFP) process by incorporating all criteria needed to evaluate, select, utilize and maintain relationships with software providers. The ISG Buyers Guide evaluates customer experience and the product experience in its capability and platform.
The structure of the research reflects our understanding that the effective evaluation of software providers and products involves far more than just examining product features, potential revenue or customers generated from a provider’s marketing and sales efforts. It can ensure the best long-term relationship and value achieved from a resource and financial investment We believe it is important to take a comprehensive, research-based approach, since making the wrong choice of DataOps software can raise the total cost of ownership, lower the return on investment and hamper an enterprise’s ability to reach its potential. In addition, this approach can reduce the project’s development and deployment time and eliminate the risk of relying on opinions or historical biases.
ISG Research believes that an objective review of existing and potential new software providers and products is a critical strategy for the adoption and implementation of DataOps software. An enterprise’s review should include a thorough analysis of both what is possible and what is relevant. We urge enterprises to do a thorough job of evaluating DataOps software and offer this Buyers Guide as both the results of our in-depth analysis of these providers and as an evaluation methodology.
How To Use This Buyers Guide
Evaluating Software Providers: The Process
We recommend using the Buyers Guide to assess and evaluate new or existing software providers for your enterprise. The market research can be used as an evaluation framework to assess existing approaches and software providers or establish a formal request for information from providers on products and customer experience and will shorten the cycle time when creating an RFI. The steps listed below provide a process that can facilitate best possible outcomes in the most efficient manner.
- Define the business case and goals.
Define the mission and business case for investment and the expected outcomes from your organizational and technological efforts.
- Specify the business and IT needs.
Defining the business and IT requirements helps identify what specific capabilities are required with respect to people, processes, information and technology.
- Assess the required roles and responsibilities.
Identify the individuals required for success at every level of the enterprise from executives to frontline workers and determine the needs of each.
- Outline the project’s critical path.
What needs to be done, in what order and who will do it? This outline should make clear the prior dependencies at each step of the project plan.
- Ascertain the technology approach.
Determine the business and technology approach that most closely aligns to your enterprise’s requirements.
- Establish software provider evaluation criteria.
Utilize the product experience: capability and platform with support for adaptability, manageability, reliability and usability, and the customer experience in TCO/ROI and Validation.
- Evaluate and select the software provider and products properly.
Apply a weighting the evaluation categories in the evaluation criteria to reflect your enterprise’s priorities to determine the short list of software providers and products. - Establish the business initiative team to start the project.
Identify who will lead the project and the members of the team needed to plan and execute it with timelines, priorities and resources.
Using the ISG Buyers Guide and process provides enterprises a clear, structured approach to making smarter software and business investment decisions. It ensures alignment between strategy, people, processes and technology while reducing risk, saving time and improving outcomes. The ISG approach promotes data-driven decision-making and collaboration, helping choose the right software providers for maximum value and return on investment.
DataOps
As enterprises embracing artificial intelligence move from initial pilots and trial projects through deployment and into production at scale, many are realizing the critical importance of agile and responsive data processes. These processes are often combined with tools and platforms that facilitate data management and processing to improve trust in the data used for AI and business intelligence.
This has led to increased attention on the role of data operations, which ISG Research defines as the application of agile development, DevOps and lean manufacturing by data engineering professionals in support of data production. DataOps encompasses the development, testing, deployment and orchestration of data integration and processing pipelines, along with improved data quality and validity via data monitoring and observability, enabling the creation and consumption of data products.
DataOps has been part of the lexicon of the data market for almost a decade. It takes inspiration from DevOps, which describes a set of tools, practices and a philosophy used to support the continuous delivery of software applications in the face of constant change. Similarly, DataOps describes a set of tools, practices and a philosophy used to support the continuous processing and delivery of data in the face of constant change.
Interest in DataOps is growing. ISG Research asserts that through 2027 more than one-half of enterprises will have adopted agile and collaborative data operations practices to facilitate responsiveness, avoid repetitive tasks, and accelerate AI initiatives. A variety of products, practices and processes enable DataOps, including products that support agile and continuous delivery of data analytics and AI and continuous, measurable improvement.
It is this emphasis on agility, collaboration and automation that in part separates DataOps from traditional approaches to data management, which typically included batch-based, manual and rigid tools and practices. Almost one-half (49%) of participants in ISG’s 2025 Market Lens Data and AI Program Study agree that data operations should be managed separately from other parts of the IT estate.
However, the distinction between DataOps and traditional data management tools is clearer in theory than in practice. In recent years many providers of traditional data management have incorporated capabilities that make products more automated, collaborative and agile. There is no industry-wide consensus on the level of agility, collaboration and automation that must be provided for products to be considered part of the DataOps category.
In seeking to define DataOps, proponents have focused on the practical application of agile development, DevOps and lean manufacturing to the tasks and skills employed by data engineering professionals in support of data analytics development and operations. This definition emphasizes specific capabilities such as continuous delivery of analytic insight, process simplification, code generation, automation to avoid repeated errors and reduced repetitive tasks, the incorporation of stakeholder feedback and advancement and measurable improvement in the efficient generation of insight from data. The practical definition of DataOps provides a set of criteria for agile and collaborative practices that products and services can be measured against.
The practical definition of DataOps provides a set of criteria for agile and collaborative practices that products and services can be measured against.
Based on our interaction with the software provider and user communities, ISG Research has adopted this set of criteria as a core component of our DataOps coverage and the capabilities against which DataOps products are evaluated in this Buyers Guide. Our criteria are focused on the collaboration, automation, acceleration and ecosystem integration capabilities required to ensure the delivery of agile BI and AI data products through the creation and orchestration of data processing pipelines, incorporating improved data reliability and integrity via data monitoring and observability. These are the key criteria we used to assess DataOps products and services as part of this Buyer’s Guide.
This research is comprised of parallel evaluations of products addressing each of the four core areas of functionality: data pipelines, data orchestration, data observability and data products. Additionally, we evaluated all products in all categories in relation to their support for DataOps practices that address collaboration, automation, acceleration and ecosystem integration
The development, testing and deployment of data pipelines is a fundamental accelerator of data-driven strategies, enabling enterprises to extract data generated by operational applications used to run the business and transport it into the analytic data platforms used to analyze operations. ISG Research defines data pipelines as the systems used to transport, process and deliver data produced by operational data platforms and applications into analytic data platforms and applications for consumption. Healthy data pipelines are necessary to ensure data is ingested, processed and loaded in the sequence required to generate BI and AI.
Given the increasing complexity of evolving data sources and requirements, it is essential to automate and coordinate the creation, scheduling and monitoring of data pipelines as part of a DataOps approach to data management. This is the realm of data orchestration, which ISG Research defines as providing the capabilities to automate and accelerate the flow of data to support operational and analytics initiatives and drive business value via capabilities for the monitoring and management of data pipelines and associated workflow.
Maintaining data quality and trust is a perennial data management challenge, often preventing enterprises from operating at the speed of business.
Maintaining data quality and trust is a perennial data management challenge, often preventing enterprises from operating at the speed of business. In addition to automating and coordinating the creation, scheduling and monitoring of data pipelines via data orchestration, it is also critical to monitor the quality and reliability of the data flowing through those data pipelines. This is achieved using data observability, which ISG Research defines as providing the capabilities for monitoring the quality and reliability of data used for analytics and governance projects as well as the reliability and health of the overall data environment. ISG asserts that through 2027, enterprises will prioritize adoption of DataOps products that address combination of data pipeline development, data orchestration and data observability, reducing the complexity and cost of using multiple tools.
The metrics generated by data observability also form a critical component of the development and sharing of data products, providing the information by which data consumers can gauge if a data product meets their requirements in terms of a variety of attributes including validity, uniqueness, timeliness, consistency, completeness and accuracy.
ISG Research defines data products as the outcome of data initiatives developed with product thinking and delivered as reusable assets that can be discovered and consumed by others on a self-service basis, along with associated data contracts and feedback options. Key capabilities for platforms that enable the development of data products include a dedicated interface for the development and classification of data products and data contracts as well as a dedicated interface for the self-service discovery and consumption of data products and data contracts. Data product platforms should also include the ability for consumers of data products to provide feedback, comments and ratings as well as request improvements or new products, and the ability for data owners to monitor data product usage and performance metrics and view and manage requests for data product modifications and the development of new data products.
As always, however, software products are only one aspect of delivering on the promise of DataOps. New approaches to people, processes and information are also required to deliver agile and collaborative development, testing and deployment of data and analytics workloads, as well as data operations. To improve the value generated from analytics and data initiatives, enterprises need to adopt processes and methodologies that support rapid innovation and experimentation, automation, collaboration, measurement and monitoring, and high data quality.
The ISG Buyers Guide™ for DataOps evaluates software providers and products to address data pipeline development, testing and deployment, data pipeline orchestration, data pipeline observability, and data products. Providers with products that address at least three elements—data pipelines, data orchestration, data observability or data products—were deemed to provide a superset of functionality to address DataOps overall.
This research evaluates the following software providers that offer products to address key elements of DataOps as we define it: Alteryx, AWS, Databricks, DataOps.live, IBM, Informatica, K2view, Microsoft, Palantir, Pentaho, Qlik, SAP, Snowflake and Tencent Cloud.
Key Takeaways
DataOps has emerged as a central discipline for enterprises seeking to accelerate AI initiatives and maintain trust in data across complex environments. As organizations pursue agility and automation in data management, DataOps enables continuous delivery of data products and insight at scale. The ISG Buyers Guide™ for DataOps underscores how integrated pipeline development, orchestration and observability capabilities are reshaping enterprise data operations. These solutions help enterprises build a resilient foundation for data-driven innovation.
Software Provider Summary
The ISG Buyers Guide™ for DataOps evaluates software providers offering products that support data pipeline development, orchestration, observability and data product management. The research assessed 14 providers, with Pentaho ranking highest overall, followed by Databricks and Informatica. Providers were evaluated on Product Experience and Customer Experience criteria and this report provides the results for each provider along with strengths and areas for improvement.
Product Experience Insights
Product Experience measures how effectively providers support the complete lifecycle of onboarding, configuration, operation and maintenance of DataOps products. Leaders in this category—Pentaho, Databricks and IBM—demonstrated strength in both capability and platform criteria. The Capability assessment examined more than 245 function points across 20 sections, while the Platform assessment evaluated adaptability, manageability, reliability and usability. Leaders demonstrated robust, scalable architectures and strong integration across business and IT environments.
Customer Experience Value
Customer Experience evaluates provider commitment, viability and customer success across engagement lifecycles. Databricks, Informatica and Alteryx achieved the highest ratings for customer focus, transparency and overall value delivery. Providers that did not perform as well typically lacked clarity in articulating customer commitments or failed to provide sufficient validation of results. These shortcomings often reflected limited visibility into customer programs or inconsistent support structures.
Strategic Recommendations
Enterprises adopting DataOps should prioritize providers with proven automation and orchestration capabilities to ensure agility and responsiveness. Selecting platforms that unify pipeline management, observability and data product development can reduce operational complexity. Enterprises should also assess the provider’s commitment to customer experience to ensure sustained value and measurable ROI. Effective DataOps investments should advance collaboration, trust and innovation across the organization.
The Findings – DataOps
The software providers and products evaluated in the research provide product and customer experiences, but not everything offered is equally valuable to every enterprise or is needed to operate in business processes and use cases. Moreover, the existence of too many capabilities in products may be a negative factor for an enterprise if it introduces unnecessary complexity. Nonetheless, you may decide that a more comprehensive set of capabilities in the product is important, and where they match your enterprise’s requirements.
An effective customer relationship with a software provider is vital to the success of any investment. The overall customer experience and the full lifecycle of engagement play a key role in ensuring satisfaction and long-term success. Providers with dedicated customer leadership, such as chief customer officers, tend to invest more deeply in these relationships and prioritize customer outcomes to TCO and ROI expectations. It is equally important that this commitment to customer success is clearly demonstrated throughout the provider’s website, buying process and customer journey.
Overall Scoring of Software Providers Across Categories
The research finds Pentaho atop the list, followed by Databricks and Informatica. Providers that place in the top three of a category earn the designation of Leader. Databricks has done so in four categories; Informatica and Pentaho in three; IBM in two and Alteryx, DataOps.live and Microsoft in one category.
The overall representation of the research below places the rating of the Product Experience and Customer Experience on the x and y axes, respectively, to provide a visual representation and classification of the software providers. Those providers whose Product Experience have above median weighted performance to the axis in aggregate of the two product categories place farther to the right, while the performance and weighting for the Customer Experience category determines placement on the vertical axis. In short, software providers that place closer to the upper-right on this chart performed better than those closer to the lower-left.
The research categorizes and rates software providers into one of four categories: Assurance, Exemplary, Merit or Innovative. This represents the software providers’ weighted performance in meeting the requirements in product and customer experience.
Exemplary: This rating (upper right) represents those that performed above median in Product and Customer Experience requirements. The providers rated Exemplary are: Alteryx, Databricks, IBM, Informatica, Microsoft and Pentaho.
Innovative: This rating (lower right) represents those that performed above median in Product Experience but not in Customer Experience. The provider rated Innovative is: DataOps.live.
Assurance: This rating (upper left) represents those that performed above median in Customer Experience but not in Product Experience. The providers rated Assurance are: AWS and SAP.
Merit: This rating (lower left) represents those that did not surpass the median in Customer or Product Experience. The providers rated Merit are: K2view, Palantir, Qlik, Snowflake and Tencent Cloud.
We advise enterprises to use this research as a supplement to their own evaluations, recognizing that ratings or rankings do not solely represent the value of a provider nor indicate universal suitability of a set of products.
Product Experience
The process of researching products to address an enterprise’s needs should be comprehensive and evaluate specific capabilities and the underlying platform to the product experience. Our evaluation of the Product Experience examines the lifecycle of onboarding, configuration, operations, usage and maintenance. Too often, software providers are not evaluated for the entirety of the product; instead, they are evaluated on market execution and vision of the future.
The research results in Product Experience are ranked at 80%, or four-fifths, using the underlying weighted performance. Importance was placed on the categories as follows: Capability (30%) and Platform (50%). Pentaho, Databricks and IBM were designated Product Experience Leaders.
Customer Experience
The importance of a customer relationship with a software provider is essential to the actual success of the products and technology. The evaluation of the Customer Experience and the entire lifecycle an enterprise has with its software provider is critical for ensuring satisfaction in working with that provider. The ISG Buyers Guide examines a software provider’s customer commitment, viability, customer success, sales and onboarding, product roadmap and services with partners and support. The customer experience category also investigates the TCO/ROI and how well a software provider demonstrates the product’s overall value, cost and benefits, including the tools and resources to evaluate these factors.
The research results in Customer Experience are ranked at 20%, or one-fifth of the 100% index, and represent the underlying provider validation and TCO/ROI requirements as they relate to the framework of commitment and value to the software provider-customer relationship.
The software providers that evaluated the highest in the Customer Experience category are Databricks, Informatica and Alteryx. These category leaders best communicate commitment and dedication to customer needs.
Software providers that did not perform well in this category were unable to provide or make sufficient information readily available to demonstrate success or articulate their commitment to customer experience. The use of a software provider requires continuous investment, so a holistic evaluation must include examination of how they support their customer experience.
Software Provider Inclusion – DataOps
For inclusion in the 2025 ISG Buyers Guide™ for DataOps, a software provider must be in good standing financially and ethically, have at least $10 million in annual or projected revenue verified using independent sources, sell products and provide support on at least two continents, and have at least 50 employees. The principal source of the relevant business unit’s revenue must be software-related, and there must have been at least one major software release in the last 12 months.
Data Operations (DataOps) focuses on the application of agile development, DevOps and lean manufacturing by data engineering professionals in support of data production. DataOps encompasses the development, testing, deployment and orchestration of data integration and processing pipelines, along with improved data quality and validity via data monitoring and observability, enabling the development and consumption of data products.
To be included in the Data Operations Buyers Guide, the product(s) must be marketed as a data operations platform or address the following functional areas, which are mapped into Buyers Guide capability criteria:
- DataOps
- Collaboration
- Acceleration
- Automation
- Ecosystem integration
- At least three of
- Data pipelines
- Data orchestration
- Data observability
- Data products
The research is designed to be independent of the specifics of software provider packaging and pricing. To represent the real-world environment in which businesses operate, we include providers that offer suites or packages of products that may include relevant individual modules or applications. If a software provider is actively marketing, selling and developing a product for the general market and it is reflected on the provider’s website that the product is within the scope of the research, that provider is automatically evaluated for inclusion.
All software providers that offer relevant products and meet the inclusion requirements were invited to participate in the evaluation process at no cost to them.
Software providers that meet our inclusion criteria but did not completely participate in our Buyers Guide were assessed solely on publicly available information. As this could have a significant impact on classification and ratings, we recommend additional scrutiny when evaluating those providers.
Products Evaluated
| Provider | Product Names | Version | Release Month/Year |
|---|---|---|---|
| Alteryx |
Alteryx One Alteryx Connect |
NA v. 2025.1 |
September 2025 May 2025 |
| AWS | Amazon SageMaker | NA | August 2025 |
| Databricks | Databricks Data Intelligence Platform | NA | September 2025 |
| DataOps.live | DataOps.live | NA | September 2025 |
| IBM | IBM watsonx.data integration | NA | September 2025 |
| Informatica | Informatica Intelligent Data Management Cloud | NA | August 2025 |
| K2view | K2view Data Product Platform | v. 8.3.0 | August 2025 |
| Microsoft |
Microsoft Fabric Microsoft Purview |
NA |
August 2025 September 2025 |
| Palantir | Palantir Foundry | NA | September 2025 |
| Pentaho |
Pentaho Data Integration Pentaho Data Quality Pentaho Data Catalog |
v. 10.2 NA v. 10.2.8 |
September 2025 September 2025 September 2025 |
| Qlik | Qlik Talend Cloud | NA | September 2025 |
| SAP | SAP Business Data Cloud | NA | September 2025 |
| Snowflake | Snowflake Platform | NA | September 2025 |
| Tencent Cloud | Tencent Cloud WeData | NA | November 2024 |
Providers of Promise
We did not include software providers that, as a result of our research and analysis, did not satisfy the criteria for inclusion in this Buyers Guide. These are listed below as “Providers of Promise.”
| Provider | Product | Annual Revenue >$10M | Operates on 2 Continents | At Least 50 Employees | Product GA |
|---|---|---|---|---|---|
| Ascend | Ascend | No | Yes | No | Yes |
| Datafold | Datafold | No | Yes | No | Yes |
| Keboola | Keboola | No | Yes | Yes | Yes |
| Nexla | Nexla | Yes | Yes | No | Yes |
| Saturam | Qualdo, Piperr | No | Yes | Yes | Yes |
Data Orchestration
While data-driven enterprises stand to gain a competitive advantage by responding faster to worker and customer demands for more innovative, data-rich applications and personalized experiences, this increasingly relies on a complex array of data pipelines to support agile, continuous data processing. Given the increasing complexity of data pipelines required to support the automation of complex business processes through agentic artificial intelligence, it is essential to coordinate the creation, scheduling and monitoring of data pipelines as part of a DataOps approach to data management.
Data orchestration modernizes traditional data management by automating how data is collected, transformed and activated across distributed environments.
This is the realm of data orchestration, which ISG Research defines as providing the capabilities to automate and accelerate the flow of data across the organization via capabilities for pipeline monitoring, pipeline management and workflow management to support operational and analytics initiatives and drive business.
Data orchestration modernizes traditional data management by automating how data is collected, transformed and activated across distributed environments. It replaces rigid, batch-based processes with agile workflows that enable real-time analytics and decision-making across multiple clouds and systems. Tools like Apache Airflow, Flyte and Metaflow—originating from digital-native innovators—have brought orchestration mainstream, helping enterprises coordinate, monitor and optimize data workflows. As data becomes more fragmented and real-time, orchestration serves as the backbone for efficient, responsive data movement and supports the growing emphasis on data literacy and democratization.
Now central to DataOps ecosystems, orchestration unifies pipeline management, observability and workflow automation to reduce complexity and enhance agility. It also powers AI and ML operations by automating data flows between models, applications and repositories. Though still early in adoption, orchestration is emerging as a cornerstone of enterprise data modernization, enabling faster insights, better collaboration and greater trust in data quality.
The ISG Buyers Guide™ for Data Orchestration evaluates software providers and products in key areas, including data pipeline management, workflow management and pipeline deployment. This research evaluates the following software providers that offer products to address key elements of data orchestration as we define it: Alteryx, Astronomer, AWS, BMC, Boomi, Cloudera, Databricks, DataKitchen, DataOps.live, dbt Labs, Gathr, Google Cloud, IBM, Informatica, K2View, Matillion, Microsoft, Palantir, Qlik, Saagie, SAP, Snowflake, Stonebranch, Tencent Cloud, Workato and Zoho.
Key Takeaways
Data orchestration has become foundational to DataOps and enterprise data modernization. As organizations move toward real-time analytics, AI and continuous data processing, orchestration automates and coordinates complex data flows across systems and environments. This Buyers Guide highlights how orchestration platforms unify pipeline management, observability and workflow automation to reduce complexity and improve agility. Enterprises are increasingly relying on orchestration to accelerate insights and strengthen trust in data quality.
Software Provider Summary
The ISG Buyers Guide™ for Data Orchestration evaluates software providers offering products that support data pipeline management, workflow management and pipeline monitoring. The research assessed 26 providers, with Databricks ranking highest overall, followed by Alteryx and Boomi. Providers were evaluated on Product Experience and Customer Experience criteria and this report provides the results for each provider along with strengths and areas for improvement.
Product Experience Insights
ISG’s Product Experience evaluation, weighted at 80 percent of the overall score, focused on Capability and Platform performance. Databricks, Pentaho and Alteryx emerged as Product Experience Leaders, supported by strengths in functionality breadth and operational maturity. The Capability category emphasized data pipeline management, workflow automation and monitoring, while Platform assessment centered on adaptability, manageability, reliability and usability. Leaders demonstrated robust architectures and intuitive platforms that support secure, scalable and enterprise-grade orchestration.
Customer Experience Value
Customer Experience, weighted at 20 percent of the overall index, evaluated providers’ customer commitment, viability, onboarding, services and value realization. Databricks, Informatica, Alteryx and Boomi achieved the highest results, reflecting mature engagement models and strong ROI communication. Vendors that performed lower often lacked transparency or accessible evidence of customer success and value. Non-Leader providers were challenged by inconsistent support experiences and limited demonstration of customer commitment across lifecycle stages.
Strategic Recommendations
Enterprises should evaluate data orchestration platforms through both capability depth and ecosystem fit, prioritizing secure, flexible and scalable architectures that align with DataOps principles. Given the growing importance of automation and observability, organizations should favor solutions that unify data workflow visibility across hybrid and multicloud environments. Vendors demonstrating clear customer leadership and measurable value delivery will better support long-term data modernization goals. A coordinated orchestration strategy is essential to sustaining agility and governance in enterprise-wide data operations.
The Findings – Data Orchestration
The software providers and products evaluated in the research provide product and customer experiences, but not everything offered is equally valuable to every enterprise or is needed to operate in business processes and use cases. Moreover, the existence of too many capabilities in products may be a negative factor for an enterprise if it introduces unnecessary complexity. Nonetheless, you may decide that a more comprehensive set of capabilities in the product is important, and where they match your enterprise’s requirements.
An effective customer relationship with a software provider is vital to the success of any investment. The overall customer experience and the full lifecycle of engagement play a key role in ensuring satisfaction and long-term success. Providers with dedicated customer leadership, such as chief customer officers, tend to invest more deeply in these relationships and prioritize customer outcomes to TCO and ROI expectations. It is equally important that this commitment to customer success is clearly demonstrated throughout the provider’s website, buying process and customer journey.
Overall Scoring of Software Providers Across Categories
The research finds Databricks atop the list, followed by Alteryx and Boomi. Providers that place in the top three of a category earn the designation of Leader. Databricks has done so in five categories; Alteryx in three; Informatica and Pentaho in two and Boomi, DataOps.live and Microsoft in one category.
The overall representation of the research below places the rating of the Product Experience and Customer Experience on the x and y axes, respectively, to provide a visual representation and classification of the software providers. Those providers whose Product Experience have above median weighted performance to the axis in aggregate of the two product categories place farther to the right, while the performance and weighting for the Customer Experience category determines placement on the vertical axis. In short, software providers that place closer to the upper-right on this chart performed better than those closer to the lower-left.
The research categorizes and rates software providers into one of four categories: Assurance, Exemplary, Merit or Innovative. This represents the software providers’ weighted performance in meeting the requirements in product and customer experience.
Exemplary: This rating (upper right) represents those that performed above median in Product and Customer Experience requirements. The providers rated Exemplary are: Alteryx, AWS, BMC, Boomi, Databricks, Google Cloud, IBM, Informatica, Matillion, Microsoft and Pentaho.
Innovative: This rating (lower right) represents those that performed above median in Product Experience but not in Customer Experience. The providers rated Innovative are: DataOps.live and Stonebranch.
Assurance: This rating (upper left) represents those that performed above median in Customer Experience but not in Product Experience. The providers rated Assurance are: Cloudera and SAP.
Merit: This rating (lower left) represents those that did not surpass the median in Customer or Product Experience. The providers rated Merit are: Astronomer, dbt Labs, Gathr.ai, K2view, Palantir, Qlik, Saagie, Snowflake, Tencent Cloud, Workato and Zoho.
We advise enterprises to use this research as a supplement to their own evaluations, recognizing that ratings or rankings do not solely represent the value of a provider nor indicate universal suitability of a set of products.
Product Experience
The process of researching products to address an enterprise’s needs should be comprehensive and evaluate specific capabilities and the underlying platform to the product experience. Our evaluation of the Product Experience examines the lifecycle of onboarding, configuration, operations, usage and maintenance. Too often, software providers are not evaluated for the entirety of the product; instead, they are evaluated on market execution and vision of the future.
The research results in Product Experience are ranked at 80%, or four-fifths, of the overall rating using the specific underlying weighted category performance. Importance was placed on the categories as follows: Capability (40%) and Platform (40%).
Databricks, Pentaho and Alteryx were designated Product Experience Leaders. While not a Leader, Boomi was also found to meet a broad range of enterprise product experience requirements.
Customer Experience
The importance of a customer relationship with a software provider is essential to the actual success of the products and technology. The evaluation of the Customer Experience and the entire lifecycle an enterprise has with its software provider is critical for ensuring satisfaction in working with that provider. The ISG Buyers Guide examines a software provider’s customer commitment, viability, customer success, sales and onboarding, product roadmap and services with partners and support. The customer experience category also investigates the TCO/ROI and how well a software provider demonstrates the product’s overall value, cost and benefits, including the tools and resources to evaluate these factors.
The research results in Customer Experience are ranked at 20%, or one-fifth of the 100% index, and represent the underlying provider validation and TCO/ROI requirements as they relate to the framework of commitment and value to the software provider-customer relationship.
The software providers that evaluated the highest in the Customer Experience category are Databricks, Informatica, Alteryx and Boomi. These category leaders best communicate commitment and dedication to customer needs.
Software providers that did not perform well in this category were unable to provide or make sufficient information readily available to demonstrate success or articulate their commitment to customer experience. The use of a software provider requires continuous investment, so a holistic evaluation must include examination of how they support their customer experience.
Software Provider Inclusion – Data Orchestration
For inclusion in the 2025 ISG Buyers Guide™ for Data Orchestration, a software provider must be in good standing financially and ethically, have at least $10 million in annual or projected revenue verified using independent sources, sell products and provide support on at least two continents, and have at least 50 employees. The principal source of the relevant business unit’s revenue must be software-related, and there must have been at least one major software release in the last 12 months.
Data orchestration enables the flow of data across the organization via capabilities for pipeline monitoring, pipeline management and workflow management. Given the increasing complexity of evolving data sources and requirements, it’s essential to automate and coordinate the creation, scheduling and monitoring of data pipelines.
To be included in the Data Orchestration Buyers Guide, the product(s) must be marketed as a data orchestration platform or address the following functional areas, which are mapped into Buyers Guide capability criteria:
- DataOps
- Collaboration
- Acceleration
- Automation
- Ecosystem integration
- Data pipeline management
- Data workflow management
- Data pipeline monitoring
The research is designed to be independent of the specifics of software provider packaging and pricing. To represent the real-world environment in which businesses operate, we include providers that offer suites or packages of products that may include relevant individual modules or applications. If a software provider is actively marketing, selling and developing a product for the general market and it is reflected on the provider’s website that the product is within the scope of the research, that provider is automatically evaluated for inclusion.
All software providers that offer relevant products and meet the inclusion requirements were invited to participate in the evaluation process at no cost to them.
Software providers that meet our inclusion criteria but did not completely participate in our Buyers Guide were assessed solely on publicly available information. As this could have a significant impact on classification and ratings, we recommend additional scrutiny when evaluating those providers.
Products Evaluated
| Provider | Product Names | Version | Release Month/Year |
|---|---|---|---|
| Alteryx | Alteryx One | NA | September 2025 |
| Astronomer | Astro | NA | August 2025 |
| AWS | Amazon SageMaker | NA | August 2025 |
| BMC | BMC Control-M | v. 9.0.22 | August 2025 |
| Boomi | Boomi Enterprise Platform | NA | August 2025 |
| Cloudera | Cloudera Data Engineering | v. 1.24.1-H1 | July 2025 |
| Databricks | Databricks Data Intelligence Platform | NA | September 2025 |
| DataOps.live | DataOps.live | NA | September 2025 |
| dbt Labs | dbt | NA | August 2025 |
| Gathr.ai | Gathr | v. 7.5.0 | September 2025 |
| Google Cloud | Google Cloud Composer | NA | September 2025 |
| IBM | IBM watsonx.data integration | NA | September 2025 |
| Informatica | Informatica Intelligent Data Management Cloud | NA | August 2025 |
| K2view | K2view Data Product Platform | v. 8.3.0 | August 2025 |
| Matillion | Matillion Data Productivity Cloud | NA | September 2025 |
| Microsoft | Microsoft Fabric | NA | August 2025 |
| Palantir | Palantir Foundry | NA | September 2025 |
| Pentaho | Pentaho Data Integration | v. 10.2 | September 2025 |
| Qlik | Qlik Talend Cloud | NA | September 2025 |
| Saagie | Saagie | v. 2025.02 | June 2025 |
| SAP | SAP Business Data Cloud | NA | September 2025 |
| Snowflake | Snowflake Platform | NA | September 2025 |
| Stonebranch | Universal Automation Center | v. 7.8.0.0 | August 2025 |
| Tencent Cloud | Tencent Cloud WeData | NA | November 2024 |
| Workato | Workato | NA | September 2025 |
| Zoho | Zoho DataPrep | v.2.0 | July 2025 |
Providers of Promise
We did not include software providers that, as a result of our research and analysis, did not satisfy the criteria for inclusion in this Buyers Guide. These are listed below as “Providers of Promise.”
| Provider | Product | Annual Revenue >$10M | Operates on 2 Continents | At Least 50 Employees | Product GA |
|---|---|---|---|---|---|
| Ascend | Ascend | No | Yes | No | Yes |
| Dagster Labs | Dagster+ | No | Yes | No | Yes |
| Datacoves | Datacoves | No | Yes | No | Yes |
| Datafold | Datafold | No | Yes | No | Yes |
| Keboola | Keboola | No | Yes | Yes | Yes |
| Nexla | Nexla | Yes | Yes | No | Yes |
| Prefect | PrefectCloud | No | Yes | No | Yes |
| Promethium | Promethium | No | Yes | No | Yes |
| PurpleCube AI | PurpleCube AI | No | Yes | No | Yes |
| Saturam | Piperr | No | Yes | Yes | Yes |
Data Pipelines
The development, testing and deployment of data pipelines is a fundamental accelerator of data-driven strategies. The pipelines enable enterprises to extract data generated by operational applications that run the business and deliver it into the analytic data platforms used to analyze the business.
ISG Research defines data pipelines as the systems used to transport, process and deliver data produced by operational data platforms and applications into analytic data platforms and applications for consumption. Healthy data pipelines are necessary to ensure data is ingested, processed and loaded in the sequence required to generate business intelligence and artificial intelligence (AI).
Data pipelines, long central to data management, are now critical to modern enterprises that depend on continuous, data-driven decision-making.
Data pipelines, long central to data management, are now critical to modern enterprises that depend on continuous, data-driven decision-making. They facilitate the flow of data across systems—extracting, transforming, and loading it for analysis—and are increasingly automated through orchestration tools that manage complex workflows. As organizations confront data silos and fragmentation, agile and well-orchestrated pipelines, often integrated with DataOps and observability platforms, have become essential. These systems not only automate development, testing, and deployment but also monitor data quality and pipeline health, reducing operational complexity and enabling trusted, enterprise-wide data access.
Evolving data processing needs are driving the shift from traditional batch ETL to more flexible ELT, zero-ETL and change data capture (CDC) approaches. ELT pushes transformations to the target platform for greater adaptability, while zero-ETL enables near real-time analytics by minimizing preprocessing. CDC further enhances agility by synchronizing incremental data changes instead of entire datasets. Together, these methods—supported by automation, orchestration and emerging AI capabilities—are transforming data pipelines into intelligent, self-optimizing systems. Generative AI, in particular, shows promise for automating pipeline creation, documentation, and integration with AI-driven business processes, signaling the next stage of acceleration in data operations.
The ISG Buyers Guide™ for Data Pipelines evaluates software providers and products in key areas, including data pipeline development, data pipeline testing, and data pipeline deployment. This research evaluates the following software providers that offer products to address key elements of data pipelines as meet our definition: Airbyte, Alteryx, Astronomer, AWS, BMC, Boomi, Databricks, DataKitchen, DataOps.live, dbt Labs, Fivetran, Gathr, Google Cloud, IBM, Informatica, K2view, Kleene, Matillion, Microsoft, Palantir, Qlik, SAP, Snowflake, Tencent Cloud, Workato and Zoho.
Key Takeaways
Enterprises depend on well-orchestrated data pipelines to connect operational and analytic systems, ensuring the continuous flow of trusted data that powers business intelligence and AI. Modern pipelines have evolved beyond traditional batch processing to support real-time and event-driven models using ELT, zero-ETL and change data capture. These approaches improve agility and scalability while reducing complexity. As automation and AI become embedded across orchestration, monitoring and optimization, data pipelines are emerging as intelligent systems that sustain enterprise-wide data operations.
Software Provider Summary
The ISG Buyers Guide™ for Data Pipelines evaluates software providers offering products that support data pipeline development, testing and deployment. The research assessed 26 providers, with Databricks ranking highest overall, followed by Informatica and IBM. Providers were evaluated on Product Experience and Customer Experience criteria and this report provides the results for each provider along with strengths and areas for improvement.
Product Experience Insights
ISG Research weighted Product Experience at 80 percent of the overall rating, emphasizing Capability and Platform as core factors. Databricks, IBM, Pentaho and Informatica were designated Product Experience Leaders. Databricks, Informatica and Microsoft led in Platform for delivering adaptable, reliable and user-friendly foundations, while DataOps.live, Databricks and Pentaho led in Capability for broad functional coverage. Leaders demonstrated robust integration, governance and usability across complex enterprise environments.
Customer Experience Value
Customer Experience accounted for 20 percent of the evaluation, measuring provider commitment, viability and total cost of ownership. Databricks, Informatica, Alteryx and Boomi achieved the highest scores, supported by clear communication of customer value and strong success enablement. Non-Leader providers struggled to make customer success information accessible or lacked evidence of measurable ROI, with challenges most apparent in service transparency and partner engagement.
Strategic Recommendations
Enterprises should select data pipeline platforms that balance automation, governance and flexibility to scale across hybrid and multicloud environments. Integrating pipeline orchestration with DataOps and observability tools enhances data trust and system reliability. Organizations modernizing from ETL to ELT or CDC should prioritize products that minimize latency while maintaining governance controls. Investing in providers that combine platform maturity with demonstrated customer success will deliver long-term adaptability and measurable business outcomes.
The Findings – Data Pipelines
The software providers and products evaluated in the research provide product and customer experiences, but not everything offered is equally valuable to every enterprise or is needed to operate in business processes and use cases. Moreover, the existence of too many capabilities in products may be a negative factor for an enterprise if it introduces unnecessary complexity. Nonetheless, you may decide that a more comprehensive set of capabilities in the product is important, and where they match your enterprise’s requirements.
An effective customer relationship with a software provider is vital to the success of any investment. The overall customer experience and the full lifecycle of engagement play a key role in ensuring satisfaction and long-term success. Providers with dedicated customer leadership, such as chief customer officers, tend to invest more deeply in these relationships and prioritize customer outcomes to TCO and ROI expectations. It is equally important that this commitment to customer success is clearly demonstrated throughout the provider’s website, buying process and customer journey.
Overall Scoring of Software Providers Across Categories
The research finds Databricks atop the list, followed by Informatica and IBM. Providers that place in the top three of a category earn the designation of Leader. Databricks has done so in five categories; Informatica in three; IBM and Pentaho in two; and Alteryx, DataOps.live, and Microsoft in one category.
The overall representation of the research below places the rating of the Product Experience and Customer Experience on the x and y axes, respectively, to provide a visual representation and classification of the software providers. Those providers whose Product Experience have above median weighted performance to the axis in aggregate of the two product categories place farther to the right, while the performance and weighting for the Customer Experience category determines placement on the vertical axis. In short, software providers that place closer to the upper-right on this chart performed better than those closer to the lower-left.
The research categorizes and rates software providers into one of four categories: Assurance, Exemplary, Merit or Innovative. This represents the software providers’ weighted performance in meeting the requirements in product and customer experience.
Exemplary: This rating (upper right) represents those that performed above median in Product and Customer Experience requirements. The providers rated Exemplary are: Alteryx, Boomi, Databricks, DataOps.live, Google Cloud, IBM, Informatica, Matillion, Microsoft, Pentaho and SAP.
Innovative: This rating (lower right) represents those that performed above median in Product Experience but not in Customer Experience. The providers rated Innovative are: dbt Labs and Palantir.
Assurance: This rating (upper left) represents those that performed above median in Customer Experience but not in Product Experience. The providers rated Assurance are: AWS, BMC, Qlik and Workato.
Merit: This rating (lower left) represents those that did not surpass the median in Customer or Product Experience. The providers rated Merit are: Airbyte, Astronomer, Fivetran, Gathr.ai, K2view, Kleene, Snowflake, Tencent Cloud and Zoho.
We advise enterprises to use this research as a supplement to their own evaluations, recognizing that ratings or rankings do not solely represent the value of a provider nor indicate universal suitability of a set of products.
Product Experience
The process of researching products to address an enterprise’s needs should be comprehensive and evaluate specific capabilities and the underlying platform to the product experience. Our evaluation of the Product Experience examines the lifecycle of onboarding, configuration, operations, usage and maintenance. Too often, software providers are not evaluated for the entirety of the product; instead, they are evaluated on market execution and vision of the future.
The research results in Product Experience are ranked at 80%, or four-fifths, of the overall rating using the specific underlying weighted category performance. Importance was placed on the categories as follows: Capability (40%) and Platform (40%). Databricks, IBM, Pentaho and Informatica were designated Product Experience Leaders.
Customer Experience
The importance of a customer relationship with a software provider is essential to the actual success of the products and technology. The evaluation of the Customer Experience and the entire lifecycle an enterprise has with its software provider is critical for ensuring satisfaction in working with that provider. The ISG Buyers Guide examines a software provider’s customer commitment, viability, customer success, sales and onboarding, product roadmap and services with partners and support. The customer experience category also investigates the TCO/ROI and how well a software provider demonstrates the product’s overall value, cost and benefits, including the tools and resources to evaluate these factors.
The research results in Customer Experience are ranked at 20%, or one-fifth of the 100% index, and represent the underlying provider validation and TCO/ROI requirements as they relate to the framework of commitment and value to the software provider-customer relationship.
The software providers that evaluated the highest in the Customer Experience category are Databricks, Informatica, Alteryx and Boomi. These category leaders best communicate commitment and dedication to customer needs.
Software providers that did not perform well in this category were unable to provide or make sufficient information readily available to demonstrate success or articulate their commitment to customer experience. The use of a software provider requires continuous investment, so a holistic evaluation must include examination of how they support their customer experience.
Software Provider Inclusion – Data Pipelines
For inclusion in the 2025 ISG Buyers Guide™ for Data Pipelines, a software provider must be in good standing financially and ethically, have at least $10 million in annual or projected revenue verified using independent sources, sell products and provide support on at least two continents, and have at least 50 employees. The principal source of the relevant business unit’s revenue must be software-related, and there must have been at least one major software release in the last 12 months.
The development, testing and deployment of data pipelines enables enterprises to extract data from the operational applications and data platforms designed to run the business and load, integrate and transform it into the analytic data platforms and tools used to analyze the business. Data pipelines are a fundamental accelerator of data-driven strategies, and today’s analytics environments require agile data pipelines that can traverse multiple data-processing locations and evolve with business needs.
To be included in the Data Pipelines Buyers Guide, the product(s) must be marketed as a data pipelines platform or address the following functional areas, which are mapped into Buyers Guide capability criteria:
- DataOps
- Collaboration
- Acceleration
- Automation
- Ecosystem integration
- Data pipeline development
- Data pipeline testing
- Data pipeline deployment
The research is designed to be independent of the specifics of software provider packaging and pricing. To represent the real-world environment in which businesses operate, we include providers that offer suites or packages of products that may include relevant individual modules or applications. If a software provider is actively marketing, selling and developing a product for the general market and it is reflected on the provider’s website that the product is within the scope of the research, that provider is automatically evaluated for inclusion.
All software providers that offer relevant products and meet the inclusion requirements were invited to participate in the evaluation process at no cost to them.
Software providers that meet our inclusion criteria but did not completely participate in our Buyers Guide were assessed solely on publicly available information. As this could have a significant impact on classification and ratings, we recommend additional scrutiny when evaluating those providers.
Products Evaluated
| Provider | Product Names | Version | Release Month/Year |
|---|---|---|---|
| Airbyte | Airbyte | v. 1.8 | August 2025 |
| Alteryx | Alteryx One | NA | September 2025 |
| Astronomer | Astro | NA | August 2025 |
| AWS | Amazon SageMaker | NA | August 2025 |
| BMC | BMC Control-M | v. 9.0.22 | August 2025 |
| Boomi | Boomi Enterprise Platform | NA | August 2025 |
| Databricks | Databricks Data Intelligence Platform | NA | September 2025 |
| DataOps.live | DataOps.live | NA | September 2025 |
| dbt Labs | Dbt | NA | August 2025 |
| Fivetran | Fivetran | NA | September 2025 |
| Gathr.ai | Gathr | 7.5.0 | September 2025 |
| Google Cloud | Google Cloud Composer | NA | September 2025 |
| IBM | IBM watsonx.data integration | NA | September 2025 |
| Informatica | Informatica Intelligent Data Management Cloud | NA | August 2025 |
| K2view | K2view Data Product Platform | v. 8.3.0 | August 2025 |
| Kleene | Kleene | NA | September 2025 |
| Matillion | Matillion Data Productivity Cloud | NA | September 2025 |
| Microsoft | Microsoft Fabric | NA | August 2025 |
| Palantir | Palantir Foundry | NA | September 2025 |
| Pentaho | Pentaho Data Integration | v. 10.2 | September 2025 |
| Qlik | Qlik Talend Cloud | NA | September 2025 |
| SAP | SAP Business Data Cloud | NA | September 2025 |
| Snowflake | Snowflake Platform | NA | September 2025 |
| Tencent Cloud | Tencent Cloud WeData | NA | November 2024 |
| Workato | Workato | NA | September 2025 |
| Zoho | Zoho DataPrep | v. 2.0 | July 2025 |
Providers of Promise
We did not include software providers that, as a result of our research and analysis, did not satisfy the criteria for inclusion in this Buyers Guide. These are listed below as “Providers of Promise.”
| Provider | Product | Annual Revenue >$10M | Operates on 2 Continents | At Least 50 Employees | Product GA |
|---|---|---|---|---|---|
| Arch Data | Meltano | No | Yes | No | Yes |
| Ascend | Ascend | No | Yes | No | Yes |
| Dagster Labs | Dagster+ | No | Yes | No | Yes |
| Datacoves | Datacoves | No | Yes | No | Yes |
| Datafold | Datafold | No | Yes | No | Yes |
| FirstEigen | DataBuck | No | Yes | No | Yes |
| Integrate.io | Integrate.io | No | Yes | Yes | Yes |
| Keboola | Keboola | No | Yes | Yes | Yes |
| Mage Technologies | Mage | No | Yes | No | Yes |
| Mozart Data | Mozart Data | No | Yes | No | Yes |
| Nexla | Nexla | Yes | Yes | No | Yes |
| Pipedream | Pipedream | No | Yes | No | Yes |
| Prefect | PrefectCloud | No | Yes | No | Yes |
| Promethium | Promethium | No | Yes | No | Yes |
| PurpleCube AI | PurpleCube AI | No | Yes | No | Yes |
| Saturam | Piperr | No | Yes | Yes | Yes |
| Switchboard Software | Data Automation | No | Yes | No | Yes |
| Torana | iceDQ | No | Yes | No | Yes |
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