ISG Software Research recently published the 2025 Buyers Guide for Real-Time Data, providing an assessment of 43 software providers offering products used by analytics and data professionals to facilitate the use of real-time data. The Real-Time Data Buyers Guide research includes five reports which are focused on overall Real-Time Data, Application Integration, Messaging and Event Processing, Streaming Data and Streaming Analytics. Below I provide an overview of each of the five reports, as well as some observations on market trends.
ISG Research’s Buyers Guides evaluate software providers in seven key categories that are weighted to reflect buyers’ needs based on our expertise and research. Five are product-
experience related: Adaptability, Capability, Manageability, Reliability and Usability. In addition, we consider two customer-experience categories: Validation and Total Cost of Ownership/Return on Investment (TCO/ROI).
ISG Research defines real-time data as the sharing, processing and analysis of data communicated in messages and streams of messages generated by enterprise systems, devices and applications as business events occur.
The Real-Time Data Buyers Guide evaluated 25 providers and products based on core capabilities such as messaging and event processing, application integration, streaming data and streaming analytics. The research found AWS atop the list, followed by Google Cloud and Microsoft. Software providers that place in the top three of a category earn the designation of Leader. Oracle has done so in six categories; Informatica in five; Databricks and Google Cloud in three; Microsoft in two; and AWS and Solace in one category.
Despite the overwhelming reliance on batch data processing, it is an artificial construct driven by the historical limitations of computing capabilities to generate and process data at the same time without impacting performance. Real-time data processing enables enterprises to operate at the speed of business by acting on events as they happen.
The pressure on enterprises to improve the ability to process and analyze data in real time is exacerbated by increased demand for intelligent operational applications infused with the results of analytic processes, such as personalization and 
AI-driven recommendations. AI-driven intelligent applications require a new approach to data processing that enables real-time performance of machine learning on operational data to deliver instant, relevant information for accelerated decision-making. I assert that by 2027, more than one-third of enterprises will integrate streaming and event processing with AI and GenAI inferencing to deliver interactive real-time applications.
The Application Integration Buyers Guide assessed 22 providers and products based on key capabilities including application integration process development, application integration process deployment and application integration process management. Informatica and Oracle were Leaders in five categories; Boomi, Google Cloud, SAP and SnapLogic, in two categories; and AWS, Microsoft and Solace in one category.
ISG Research defines Application Integration as the enablement and management of direct communication between applications, supporting the fulfilment of business processes and workflows that rely on multiple applications operating in concert. Although standalone application integration and API management tools are available, most application integration and API management vendors have adopted a cloud-based integration Platform-as-a-Service (iPaaS) approach to delivering a combination of application integration, API management and data integration.
The Messaging and Event Processing Buyers Guide evaluated 15 providers products based on core capabilities such as messaging, event management and event monitoring. The research found Google Cloud atop the list, followed by AWS and Solace. Oracle was a Leader in six categories; Microsoft in five; Google cloud in three; AWS and Solace in two; and Confluent, Redpanda and Tencent Cloud in one category.
ISG Research defines messaging and event processing as the capturing of events and the sharing of information between applications, devices and systems about events as they occur. Success with messaging and events relies on the configuration of event brokers to ensure adequate scalability to meet performance, high availability and disaster recovery requirements. The proliferation of cloud computing—combined with ongoing reliance on on-premises infrastructure—makes it essential that event-driven architecture spans multiple cloud providers and hybrid architectures. Messaging and event processing are the essential foundations of an event-driven architecture and enablers of streaming data processing and streaming analytics.
The Streaming Data Buyers Guide assessed 27 providers and products based on core capabilities such as event streaming, stream processing, stream management and stream governance. The research found Databricks atop the list, followed by AWS and Microsoft. Informatica was a Leader in six categories; Databricks in four; Google Cloud in three; Microsoft and Actian in two; and Cloudera, Confluent, Cumulocity, Solace and Striim in one category.
ISG Research defines streaming data as the processing and management of continuously generated streams of event-based messages. By processing streaming data in real time, enterprises can refine and enhance streaming data and combine data from multiple event streams. Success with streaming data relies on the holistic management and governance of data in motion and data at rest. Integration with more traditional batch data processing technologies is, therefore, important to streaming data. This includes stream-table duality to maintain compatibility with database tables, the ability to materialize streaming data into an external database or data storage for long-term persistence and the analysis of real-time data streams alongside batches of historical event data.
Processing streaming data enables enterprises to act on the event data as it is communicated and forms the basis of streaming analytics. The Streaming Analytics Buyers Guide evaluated 22 providers and products based on core capabilities such as stream processing, analytics, query management and AI. The research found Databricks atop the list, followed by Oracle and Microsoft. Oracle was a Leader in six categories; Databricks in five categories; Google Cloud in three categories; Actian and Microsoft in two categories; and Cloud Software Group, Cumulocity and Palantir in one category.
ISG Research defines streaming analytics as the use of technology to analyze continuously generated streams of event-based messages to respond to opportunities or threats with timely actions. The Streaming Analytics Buyers Guide illustrated that functionality to support AI-driven intelligent applications is still emerging. More than one-half of providers graded A- or above for native ML scoring (59%) and integration with external AI and ML models and services (55%), while 32% graded A- or above for retrieval augmented generation and only 9% graded A- or above for support for agentic AI.
As always, software products are only one aspect of delivering on the promise of Real-Time Data. New approaches to people, processes and information are also required to deliver agile and collaborative development, testing, deployment and monitoring of data and analytics workloads and ensure the validity and quality of data. I recommend that enterprises evaluating Real-Time Data products should be conscious of the need develop, deliver and adopt applications and business processes designed to facilitate real-time decision-making.
Regards,
Matt Aslett
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