pgvector

7 pages in this section.

Why vector similarity search works as a Postgres extension, and how approximate nearest neighbor indexing trades recall for speed inside the planner.

Explainer Pgvector Vector Search Embeddings

pgvector Basics

Learn how pgvector adds a vector type and distance operators to PostgreSQL. Install the extension, choose a distance metric, and understand dimension limits.

Sql Pgvector Embeddings Basics Pgvector

IVFFlat vs HNSW Indexes

Compare pgvector's IVFFlat and HNSW indexes for approximate nearest neighbor search. Learn to choose based on recall, RAM, and build time.

Sql Pgvector Embeddings Ivfflat Hnsw

RAG Storage Schema

Learn to design a RAG store schema in Postgres for LLM apps. Split documents into chunks, store embeddings, and manage metadata for filtering and citations.

Sql Pgvector Embeddings Rag Storage

pgvector at Scale

Sql Pgvector Embeddings Advanced Pgvector

pgvector Best Practices

Learn pgvector best practices for production RAG, including pinning versions, optimizing indexes, benchmarking recall, and managing schema and tenancy.

Sql Pgvector Embeddings Best Practices List

pgvector Highlights Summary

A single-page roundup of every highlight bullet from the 6 pages in the pgvector section, grouped by source page so you can scan all 35 takeaways without opening each article individually.

Highlights Summary Pgvector Embeddings

pgvector

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