Providers focus on delivering platforms that span analytic-operational needs and support the comprehensive requirements for AI, new research says

Agentic and generative AI are introducing new enterprise requirements for management and use of data, and leading software providers are meeting the moment with innovative hybrid data platforms, according to new research from global AI-centered technology research and advisory firm Information Services Group (ISG) (Nasdaq: III).

The ISG Buyers Guides™ for Data Platforms, produced by ISG Software Research, provide the rankings and ratings of 38 software providers and their products to support data storage, processing, analysis and presentation. The research finds that the traditional distinction between analytic and operational data platforms is blurring as more business applications use real-time, AI-powered analytic processing for functions such as personalization, real-time predictions and contextually relevant recommendations. To enable intelligent applications driven by GenAI and machine learning, providers are delivering data platform capabilities to support hybrid operational and analytic workloads.

“Enterprises have become totally dependent on data platforms for business analysis and operations,” said Matt Aslett, director of research, Analytics, Data & AI, for ISG Software Research. “As AI expands and transforms enterprise uses of data, platforms are rapidly evolving to support the inferencing capabilities of intelligent operational applications.”

Most companies use a variety of data platforms to support a range of application requirements. Increasingly, they deploy data platforms on cloud infrastructure or consume their functionality as managed services, seeking to increase agility, the research finds. When choosing a data platform, the fundamental question companies have considered is whether it will be used for workloads that are operational (used to run the business) or analytic (used to analyze the business). Operational data platforms support functions such as finance, sales, human capital management and customer experience, while analytic platforms serve workloads such as business intelligence, decision support and data science.

Different data platform architectures have evolved to maximize query performance for each category of workload. However, ISG predicts that through 2027, data platform providers will prioritize the development of hybrid operational and analytic functionality to fulfill new application requirements created by GenAI. Providers will deliver a combination of these types of functionality with either one or a set of data platform products. These moves will address market demand: By 2027, ISG expects two-thirds of enterprises to adopt new operational database products to meet the AI requirements of intelligent applications.

As hybrid capabilities become available in operational data platforms, enterprises will still need separate analytic data platforms for business intelligence and data science projects, the research finds. There is also a growing need for these platforms to support the development, training and tuning of ML and GenAI models.

For its 2025 Buyers Guides for Data Platforms, ISG evaluated software providers across three platform categories — Data Platforms, Analytic Data Platforms and Operational Data Platforms — and produced a separate Buyers Guide for each. A total of 38 providers were assessed: Actian, Aerospike, Aiven, Alibaba Cloud, AWS, Broadcom, Cloudera, Cockroach Labs, Couchbase, Databricks, Dremio, EDB, Google Cloud, Huawei Cloud, IBM, IBM DataStax, Incorta, InterSystems, KX, MariaDB, Microsoft, MongoDB, Neo4j, OpenText, Oracle, Percona, PingCAP, Progress Software, Redis, Salesforce, SAP, SingleStore, Snowflake, Starburst, Tencent Cloud, Teradata, VAST Data and Yugabyte.

ISG Software Research rates software providers in seven evaluation categories. Five are related to product experience: usability, manageability, reliability, capability and adaptability. Two are related to customer assurance: validation and total cost of ownership and return on investment (TCO/ROI). Providers ranked in the top three for each evaluation category are named as Leaders. Within each platform category, those with the most Leader rankings are named as Overall Leaders.

The Overall Leaders of the 2025 Buyers Guides™ for Data Platforms were the following:

Data Platforms: Oracle was the top Overall Leader, followed by InterSystems and Google Cloud. Oracle was designated a Leader in six evaluation categories, InterSystems in four and Google Cloud in three. The three top Overall Leaders all were rated Exemplary, along with Actian, AWS, Cloudera, Couchbase, IBM, Microsoft and SAP. Alibaba Cloud, Broadcom and Progress Software were rated Innovative.

Analytic Data Platforms: Databricks was the top Overall Leader, followed by Oracle and Google Cloud. Databricks was designated a Leader in seven evaluation categories, Oracle in six and Google Cloud in three. The three top Overall Leaders all were rated Exemplary, along with Actian, AWS, Cloudera, Couchbase, IBM, InterSystems, Microsoft, SAP, Snowflake and Teradata. Broadcom, OpenText and Progress Software were rated Innovative.

Operational Data Platforms: Oracle was the top Overall Leader, followed by InterSystems and Google Cloud. Oracle was designated a Leader in six evaluation categories, InterSystems in four and Google Cloud in three. The three top Overall Leaders all were rated Exemplary, along with Actian, AWS, Cloudera, Couchbase, IBM, Microsoft, MongoDB, SAP and Yugabyte. Alibaba Cloud, Broadcom and Progress Software were rated Innovative.

“Enterprises need modern data platforms to support the diverse set of needs for operations and decision-making, and the direct set of requirements for AI,” said Mark Smith, partner and chief software analyst, ISG Software Research. “This research found shifts in which software providers are evolving to support the pressing data needs for AI and operations and in what those providers are doing. It helps guide enterprises in assessing existing software and selecting the software provider that can best meet their unique requirements now and in the future.”

The ISG Buyers Guides™ for Data Platforms are the distillation of more than a year of market and product research efforts. The research is not sponsored or influenced by software providers and is conducted solely to help enterprises optimize their business and IT software investments.

Visit this webpage to learn more about the ISG Buyers Guides™ for Data Platforms and read executive summaries of each of the three reports. The complete reports, including provider rankings across seven product and customer experience dimensions and detailed research findings on each provider, are available by contacting ISG Software Research.

About ISG Software Research

ISG Software Research provides authoritative coverage and analysis of the business and IT software industry. It distributes research and insights daily through its user community, and provides a portfolio of consulting, advisory, research and education services for enterprises, software and service providers, and investment firms. Its ISG Buyers Guides™ help enterprises evaluate and select software providers through tailored assessments powered by ISG’s proprietary methodology. Visit https://research.isg-one.com for more information and to sign up for free community membership.

About ISG

ISG (Nasdaq: III) is a global AI-centered technology research and advisory firm. A trusted partner to more than 900 clients, including 75 of the world’s top 100 enterprises, ISG is a long-time leader in technology and business services that is now at the forefront of leveraging AI to help organizations achieve operational excellence and faster growth. The firm, founded in 2006, is known for its proprietary market data, in-depth knowledge of provider ecosystems, and the expertise of its 1,600 professionals worldwide working together to help clients maximize the value of their technology investments.

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Enterprises have become dependent on data platforms for business analysis and operations. As AI expands and transforms enterprise uses of data, platforms are rapidly evolving to support the inferencing capabilities of intelligent operational applications.