Report:
The Forrester Wave™: Data Management For Analytics, Q1 2023
How does Forrester define the Data Management For Analytics market in 2023?
Data Management for Analytics (DMA) is a modern data architecture that uses integrated metadata, tiered storage, streaming, transformation, security, and governance — running on-premises or in the cloud — to deliver scalable, integrated, real-time, and self-service analytics. DMA addresses the limitations of traditional data warehouses that took years to build and failed to accommodate new business requirements around high-speed data streaming, real-time analytics, integrated analytics, large complex data sets, and self-service capabilities. Organizations want simple, agile, integrated, cost-effective, and highly automated solutions to support modern insights.
Key Facts for The Forrester Wave™: Data Management For Analytics, Q1 2023 in 2023
- Publication Date: 21-Mar-2023
- Document ID: RES178474
- Summary: In our 26-criterion evaluation of data management for analytics (DMA) providers, we identified the 14 most significant ones — Databricks, Google, HPE, IBM, Incorta, Informatica, InterSystems, Microsoft, OpenText, Oracle, SAP, SAS, Snowflake, and Teradata — and researched, analyzed, and scored them. This report shows how each provider measures up and helps data management professionals select the right one for their needs.
- Authors: Noel Yuhanna, Aaron Katz, Dan Beaton, Bill Nagel
How did the Data Management For Analytics market evolve in 2023?
- Traditional data warehouses for analytics often took years to build, deploy, and deliver benefits
- Traditional platforms have failed to accommodate new business requirements around high-speed data streaming, real-time analytics, integrated analytics, large complex data sets, and self-service capabilities
- DMA is a modern data architecture that uses integrated metadata, tiered storage, streaming, transformation, security, and governance running on-premises or in the cloud
- DMA delivers scalable, integrated, real-time, and self-service analytics
- Organizations want simple, agile, integrated, cost-effective, and highly automated solutions to support modern insights
- 14 vendors were evaluated in this Forrester Wave assessment
- Evaluation based on 26 criteria grouped into current offering, strategy, and market presence
- Vendor materials evaluated as of December 6, 2022
What product features are required to be included in this year's evaluation?
- Data management features and functionality, including high availability, security, performance, scalability, and management for analytics
- Analytical data storage for persistence, integrity, and access
- Integration with one or more vendors to support BI, reporting, and other analytics solutions
- Native tools or integrations with third-party vendors to support data loading, unloading, transformation, governance, security, and cleansing analytical data sets
- Multiple concurrent analytical queries, aggregated data sets, and integrated data access
- On-premises, public cloud, or hybrid cloud deployment
- Tools to manage and administer the DMA platform
What are the common features of top products in the Data Management For Analytics space?
No common features specified.
Scope Exclusions
- Solutions technologically tied to specific applications (enterprise resource planning, CRM, etc.)
- Solutions tied to particular BI, business performance solutions, or predictive analytics platforms
- Solutions tied to extract, transform, load functions or middleware stacks
- Solutions that require embedding in other applications
- Vendors without standalone DMA offerings
- Vendors without publicly available releases as of December 6, 2022
- Vendors with fewer than 25 enterprise paying customers
- Vendors without sufficient Forrester customer interest based on inquiry calls
Inclusion Criteria
Vendors must, among other requirements:
- An enterprise-class DMA offering with core functional components including data management features, analytical data storage, integration capabilities, native tools for data loading/transformation/governance, support for multiple concurrent queries, deployment options (on-premises, public cloud, or hybrid cloud), and management tools
- A standalone DMA solution not technologically tied to specific applications (ERP, CRM, BI, etc.) and supported as a standalone offering
- A publicly available release that was generally available as of December 6, 2022
- A referenceable install base of 25 or more enterprise paying customers with at least three customer references provided
- Forrester customer interest demonstrated through multiple mentions during inquiry calls over the past 12 months
Offering Strengths — Relative Weighting
- Architecture — 20%
- Streaming and real-time data — 15%
- Data modeling, integration, and transformation — 15%
- Security and governance — 15%
- Performance, scale, and availability — 15%
- Visualization and tools — 10%
- Use cases — 10%
Strategy Strength — Relative Weighting
- Product vision — 25%
- Execution roadmap — 20%
- Performance — 20%
- Planned enhancements — 15%
- Commercial model — 10%
- Partner ecosystem — 10%
FAQs
Q: What does this research cover?
A: This research evaluates 14 data management for analytics (DMA) providers across 26 criteria including architecture, streaming and real-time data, data modeling/integration/transformation, security and governance, performance/scale/availability, visualization and tools, use cases, product vision, execution roadmap, commercial model, and partner ecosystem. The evaluation identifies Leaders, Strong Performers, Contenders, and Challengers in the DMA market.
Q: Who should use this research?
A: Data management professionals evaluating DMA solutions should use this research to understand how each vendor measures up across key criteria and to select the right provider for their specific needs. The research helps organizations identify vendors that support real-time analytics with high-speed ingestion, deliver self-service capabilities to democratize data and analytics, and integrate data and analytics to accelerate modern business use cases. Buyers can use the Excel-based vendor comparison tool to adapt criteria weightings to their individual requirements.
Q: What are the mandatory features of vendors included in this market?
A: All vendors included in this evaluation must offer enterprise-class DMA solutions with core capabilities including: data management features (high availability, security, performance, scalability); analytical data storage for persistence, integrity, and access; integration with BI, reporting, and analytics solutions; native or third-party tools for data loading, unloading, transformation, governance, security, and cleansing; support for multiple concurrent analytical queries and aggregated data sets; deployment options spanning on-premises, public cloud, or hybrid cloud; and comprehensive tools to manage and administer the DMA platform.
Q: What are some reasons for not being included in this report?
A:
- Solutions that are not standalone offerings and require embedding in other applications
- Solutions technologically tied to specific applications, BI platforms, or middleware stacks
- Vendors without a publicly available DMA release as of December 6, 2022
- Vendors with fewer than 25 enterprise paying customers using the DMA solution
- Vendors unable to provide at least three customer references
- Vendors without sufficient Forrester customer interest demonstrated through inquiry calls over the past 12 months
- Vendors that do not actively market a DMA platform or similar solution
Q: What should buyers consider when evaluating products in this market?
A:
- Support for real-time analytics with high-speed ingestion and memory integration, including deep integration with DRAM, flash/SSD, and intelligent data tiering to optimize price/performance ratios
- Self-service capabilities to democratize data and analytics quickly, with machine learning and data intelligence to automate data management functions
- Ability to integrate data and analytics to accelerate modern business use cases, efficiently processing large data sets, log files, and streaming data from disparate platforms
- End-to-end lineage capabilities to deliver trusted and consistent insights
- Support for advanced analytics, integrated dashboards, and actionable insights
- Deployment flexibility across on-premises, cloud, hybrid cloud, and multicloud environments
- Scalability to handle growing data volumes and concurrent users
- Comprehensive security and governance capabilities
- Vendor vision, roadmap strength, and strategic direction alignment with organizational needs
Q: How has the Data Management For Analytics market evolved in 2023?
A:
- Shift from traditional data warehouses to modern DMA architectures that are simpler, more agile, integrated, cost-effective, and highly automated
- Growing demand for high-speed data streaming and real-time analytics capabilities
- Need for integrated analytics across disparate data platforms and repositories
- Increasing requirements to handle large, complex data sets at scale
- Rise of self-service analytics and democratization of data access for business users
- Adoption of machine learning (ML) and data intelligence to automate data management functions and deliver analytics quickly
- Movement toward hybrid cloud and multicloud deployment flexibility
- Focus on end-to-end lineage to deliver trusted and consistent insights
Q: What differentiates Strength of Offering vs. Strength of Strategy?
A: Strength of Current Offering (vertical axis) evaluates the vendor's existing product capabilities across technical criteria including architecture, streaming/real-time data, data modeling/integration/transformation, security/governance, performance/scale/availability, visualization/tools, and use case support. Strength of Strategy (horizontal axis) evaluates the vendor's future direction and business approach including product vision, execution roadmap, performance track record, planned enhancements, commercial/pricing model, and partner ecosystem breadth.
Reference
- Forrester, The Forrester Wave™: Data Management For Analytics, Q1 2023, 21-Mar-2023, ID RES178474
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