PostgreSQL + pgvector Product Review: RAG Performance with Vector Search

PostgreSQL + pgvector

By adding pgvector to the PostgreSQL ecosystem, semantic search and Retrieval-Augmented Generation (RAG) scenarios become manageable in the SQL pattern.

Architecture

• Embeddings table, text/document metadata
• KNN/IVFFLAT indexes and filterable search
• Multi-tenant with authorization and row-level security

Performance Tips

• Dimension and distance metric selection
• Caching and paging strategies
• Batch insert and periodic reindex

When Should It Be Preferred?

• When you want to add semantic search without breaking the existing SQL engine
• In enterprise environments where compliance and auditability are a priority

Conclusion: With pgvector, Postgres offers a practical and manageable platform for RAG.