What vector databases are best suited for RAG applications?
Leading vector databases for RAG include Pinecone as a managed cloud service with excellent scaling, Qdrant offering open-source with rich filtering and on-disk storage, Weaviate providing open-source with built-in hybrid search, Milvus for large-scale deployments with GPU acceleration, ChromaDB for lightweight embedded use perfect for prototyping, and pgvector extending PostgreSQL with vector capabilities. For production RAG, key requirements include fast approximate nearest neighbor search, metadata filtering for access control and categorization, horizontal scaling for growing document collections, and good integration with your tech stack. pgvector is compelling when you already use PostgreSQL since it avoids adding infrastructure. For enterprise deployments requiring both keyword and semantic search, Qdrant and Weaviate offer hybrid search capabilities out of the box.