The Forrester Wave™: Enterprise Data Fabric, Q1 2024
The enterprise data fabric market has evolved to support new and emerging use cases with over two dozen new vendors entering since 2022. Vendors now provide comprehensive, unified capabilities with end-to-end data management incorporating advances in generative AI/LLMs, data intelligence, persona-based UIs, semantic integration, global transaction management, and seamless integration. Enterprises leverage data fabric for customer experience, data science, IoT insights, global transactions, fraud prevention, business 360, and real-time insights. The market shows a notable shift from read-only analytical use cases toward transactional fabric with bidirectional read-and-write capabilities for modern applications.
No common features specified.
Vendors must, among other requirements:
A: This research covers a 26-criterion evaluation of 15 enterprise data fabric providers, assessing their current offerings, strategy, and market presence. The evaluation encompasses the latest innovations including generative AI/LLM capabilities, data intelligence, persona-based UIs, semantic integration, global transaction management, and seamless integration of the data fabric experience. It evaluates vendors across categories including Leaders, Strong Performers, and Contenders.
A: Data management professionals should use this research to select the right enterprise data fabric provider for their needs. It helps organizations evaluate vendors based on specific criteria such as end-to-end integration capabilities, built-in semantics for faster deployment, genAI/LLM capabilities, performance and scale, deployment options, data management features, and support for various use cases including customer 360, real-time analytics, data science, IoT insights, and operational intelligence.
A: Enterprise data fabric solutions must include comprehensive data management capabilities: data access, discovery, transformation, catalog, integration, pipeline, preparation, security, governance, and orchestration. Solutions must ingest, process, and curate data across platforms like Apache Hadoop, EDW, NoSQL, Apache Spark, data lakes, ObjectStore, and in-memory technologies. Vendors must have customers using the solution in scaled production for use cases such as real-time analytics, data integration, customer 360, data sharing/collaboration, and operational insights.
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A: Current Offering evaluates the strength of existing product capabilities including end-to-end integration, performance, scale, deployment options, data management features, and technical capabilities. Strategy evaluates forward-looking aspects including vendor vision, innovation trajectory, product roadmap, partner ecosystem strength, market adoption, and pricing approach.