What It Is, Why It Matters, and How to Choose One

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RAG databases power retrieval-augmented generation by storing, indexing, and retrieving real-time data for AI models. Traditional databases fall short because RAG requires continuous ingestion, hybrid queries combining vector search with SQL filtering, sub-second latency, and schema flexibility. A production-ready RAG database

8m read time From cratedb.com
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Table of contents
What Is a RAG Database?Why RAG Changes Database RequirementsWhy Traditional Databases Fall Short for RAGCore Capabilities of a True RAG DatabaseCommon RAG Use Cases That Stress the Database LayerHow a Unified Analytics Database Fits RAG ArchitecturesHow CrateDB Supports RAG Database ArchitecturesChoosing the Right RAG DatabaseFinal Thoughts

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