Report:
The Forrester Wave™: Data Management For Analytics Platforms, Q2 2025
How does Forrester define the Data Management For Analytics Platforms market in 2025?
Data Management for Analytics (DMA) platforms provide a flexible and scalable solution that seamlessly integrates metadata, real-time streaming, transformation, integration, quality, and security and governance capabilities. The modern DMA platform market is undergoing transformation driven by advanced automation, built-in data intelligence, and AI-powered data management capabilities. Providers recognize generative AI (genAI) as a transformative force shaping DMA through enhanced automation and intelligence. The evaluation assessed 11 providers across Leaders (Google, Oracle, Snowflake, Databricks, Teradata), Strong Performers (IBM, Amazon Web Services, Cloudera, Informatica), and Contenders (Microsoft, SAP), evaluating their current offerings, strategy, and customer feedback to help buyers select the right platform for their needs.
Key Facts for The Forrester Wave™: Data Management For Analytics Platforms, Q2 2025 in 2025
- Publication Date: 14-Apr-2025
- Document ID: c5b0352c
- Summary: In our evaluation of data management for analytics (DMA) platform providers, we identified the most significant ones and researched, analyzed, and scored them. This report shows how each provider measures up and helps you select the right one for your needs.
- Authors: Noel Yuhanna, Aaron Katz, Emily Doherty, Jen Barton
How did the Data Management For Analytics Platforms market evolve in 2025?
- AI-driven automation and intelligence are transforming the DMA platform market
- GenAI is recognized as a transformative force helping shape DMA through enhanced automation and intelligence
- Modern DMA platforms must efficiently manage structured, semi-structured, and unstructured data types
- The demand for real-time analytics continues to grow, requiring more integrated and automated solutions
- Built-in data intelligence is rapidly evolving to provide advanced features that streamline data management tasks
- DMA platforms now integrate metadata, real-time streaming, transformation, integration, quality, and security capabilities
- Natural language capabilities are enabling users to interact with data and manage platforms without highly skilled engineers
- Vendors are focusing on comprehensive data support across all formats to gain deeper insights
- The market evaluation includes 11 major providers categorized as Leaders, Strong Performers, and Contenders
What product features are required to be included in this year's evaluation?
- Broad, enterprise-level support for data management for analytics functionality. The vendor natively provides all core functions for this space and has a demonstrated track record for supporting large enterprises.
- A solution available for purchase as a standalone product. The product has its own SKU and pricing. It is not solely available as a free feature within a larger portfolio.
- Substantial data management for analytics revenue. The vendor has at least $10 million in annual revenue from the data management for analytics product in the last four quarters.
- Mindshare among Forrester's enterprise clients. Forrester clients frequently mention the product as one they are considering or shortlisting prior to a purchase. We have heard about the product from our clients in the form of inquiries, advisories, consulting engagements, and other interactions over the past 12 months. Other vendors frequently mention this vendor as a competitor in the market.
What are the common features of top products in the Data Management For Analytics Platforms space?
No common features specified.
Scope Exclusions
- Vendors without broad, enterprise-level support for all core DMA functions natively provided
- Solutions not available as standalone products with their own SKU and pricing
- Vendors with less than $10 million in annual DMA product revenue in the last four quarters
- Vendors lacking significant mindshare among Forrester's enterprise clients
- Products solely available as free features within larger portfolios
- Vendors without demonstrated track record for supporting large enterprises
- Solutions not frequently mentioned by Forrester clients in inquiries, advisories, and consulting engagements
- Vendors not commonly cited as competitors by other market participants
Inclusion Criteria
Vendors must, among other requirements:
- Broad, enterprise-level support for data management for analytics functionality with all core functions natively provided and demonstrated track record for supporting large enterprises
- Solution available for purchase as a standalone product with its own SKU and pricing, not solely available as a free feature within a larger portfolio
- At least $10 million in annual revenue from the data management for analytics product in the last four quarters
- Mindshare among Forrester's enterprise clients - frequently mentioned in inquiries, advisories, consulting engagements, and competitive discussions over the past 12 months
Offering Strengths — Relative Weighting
- Integrated DMA platform — 6%
- Deployment options — 5%
- Data persistence — 5%
- Automated management — 5%
- Generative AI/LLM — 5%
- Data pipeline — 5%
- Real-time optimization — 5%
- In-platform analytics — 5%
- Data modeling — 5%
- Data product — 5%
- Data consumers — 5%
- Data integration — 5%
- Data transformation — 5%
- Data quality — 5%
- Data access — 5%
- Data security — 5%
- Data governance — 5%
- Performance optimization — 5%
- Scale-out optimization — 5%
- Data visualization — 4%
Strategy Strength — Relative Weighting
- Vision — 35%
- Innovation — 25%
- Roadmap — 25%
- Partner ecosystem — 5%
- Adoption — 5%
- Pricing flexibility and transparency — 5%
FAQs
Q: What does this research cover?
A: This research evaluates 11 data management for analytics (DMA) platform providers, analyzing their current offerings, strategic vision, and customer feedback. The evaluation focuses on how vendors support genAI automation, built-in data intelligence, diverse data types at scale, real-time analytics, and integrated data management capabilities. It provides detailed scorecards comparing vendors across capabilities including data persistence, pipelines, quality, security, governance, visualization, and AI/ML integration.
Q: Who should use this research?
A: DMA platform customers should use this evaluation to inform purchase decisions when selecting vendors that support both short-term and long-term data strategies. Organizations looking for AI-driven automation, context-driven analytics through data intelligence, comprehensive support for all data types, real-time processing capabilities, and integrated data management solutions will find this research particularly valuable for comparing vendor strengths and identifying the best fit for their specific use cases and requirements.
Q: What are the mandatory features of vendors included in this market?
A: To be included in this Forrester Wave evaluation, vendors must provide: (1) Broad, enterprise-level support for data management for analytics functionality, natively providing all core functions with a demonstrated track record for supporting large enterprises; (2) A solution available for purchase as a standalone product with its own SKU and pricing, not solely as a free feature within a larger portfolio; (3) At least $10 million in annual revenue from the data management for analytics product in the last four quarters; and (4) Significant mindshare among Forrester's enterprise clients, being frequently mentioned in inquiries, advisories, consulting engagements, and competitive discussions over the past 12 months.
Q: What are some reasons for not being included in this report?
A:
- Lack of broad, enterprise-level support for all core DMA functions
- Solution not available as a standalone product with separate SKU and pricing
- Annual DMA product revenue below $10 million threshold
- Insufficient mindshare among Forrester's enterprise clients
- Product only available as free feature bundled within larger portfolio
- No demonstrated track record supporting large enterprise deployments
- Infrequent mentions in Forrester client inquiries, advisories, and consulting engagements
- Not commonly cited as competitor by other vendors in the market
- Declined to participate in full evaluation process (vendors may still be included with limited scoring based on primary and secondary research)
Q: What should buyers consider when evaluating products in this market?
A:
- Support genAI to automate DMA functions and accelerate use cases - look for vendors that integrate natural language capabilities to streamline management, automate data anomaly detection, support vectorized data for similarity searches, and leverage agentic AI
- Harness built-in data intelligence to drive context-driven analytics - choose vendors that offer comprehensive and automated data intelligence enabling effective data contextualization to accelerate diverse use cases like predicting customer behavior, optimizing supply chains, or preventing fraud
- Leverage all kinds of data at scale to drive new insights - select vendors who offer comprehensive data support across structured, semi-structured, and unstructured formats with robust capabilities to handle complex data types requiring sophisticated DMA engines
- Evaluate deployment flexibility across on-premises, cloud, hybrid, and multicloud environments based on your infrastructure requirements
- Assess real-time data processing and optimization capabilities for time-sensitive analytics needs
- Consider integrated platform capabilities versus point solutions requiring extensive integration work
- Review vendor roadmaps for AI/ML advancement, automation enhancements, and data intelligence features
- Examine partner ecosystems and pricing flexibility to support long-term strategic needs
- Validate data security, governance, and compliance capabilities for your industry requirements
- Test ease of use, self-service features, and natural language interfaces to democratize data access across user personas
Q: How has the Data Management For Analytics Platforms market evolved in 2025?
A:
- AI-driven automation and intelligence transforming the DMA platform landscape
- GenAI enabling new levels of sophistication in automating complex tasks like data cleansing, transformation, security, governance, and integration
- Natural language capabilities enabling users to interact with data, generate insights, and manage platforms without highly skilled engineers
- Built-in data intelligence providing advanced features that automatically identify data patterns, related data, and trends within complex datasets
- Growing demand for real-time analytics requiring increasingly integrated and automated data management solutions
- Need to leverage all kinds of data (structured, semi-structured, and unstructured) at scale to drive new insights
- Separation of compute and storage driving cost reductions and more efficient, streamlined, and agile data management
- Shift toward agentic AI for more efficient DMA operations
- Emphasis on vectorized data for similarity searches and context-driven analytics
Q: What differentiates Strength of Offering vs. Strength of Strategy?
A: Strength of Offering evaluates current product capabilities across 20 technical criteria including integrated DMA platform, deployment options, data persistence, automation, AI/LLM capabilities, data pipelines, real-time optimization, analytics, modeling, quality, security, governance, performance, and visualization. Strength of Strategy assesses forward-looking elements with heavy emphasis on vision (35%), innovation (25%), and roadmap (25%), plus partner ecosystem, adoption, and pricing flexibility. Offering focuses on what the platform can do today, while Strategy evaluates the vendor's direction, innovation capacity, and market positioning for the future.
Reference
- Forrester, The Forrester Wave™: Data Management For Analytics Platforms, Q2 2025, 14-Apr-2025, ID c5b0352c
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