The Postgres Developer's Guide to Vector Index Tradeoffs
Vector search becomes an index design problem as your data grows. Here's how to make the right call without leaving Postgres.
By Hien Phan
May 26th, 2026
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Vector search becomes an index design problem as your data grows. Here's how to make the right call without leaving Postgres.
By Hien Phan
May 26th, 2026
Most search stacks run four systems to answer one question. You don't need any of them. Build production hybrid search in Postgres with pg_textsearch for BM25, pgvectorscale for vector similarity, and Reciprocal Rank Fusion to combine them. One query. One database.
By Erin Mikail Staples
April 20th, 2026
pg_textsearch 1.0 brings native BM25 search to Postgres. No Elasticsearch sidecar needed. Learn how it works and see benchmarks vs. ParadeDB at 138M documents.
By Todd J. Green
March 31st, 2026
You don't need Elasticsearch: BM25 is now in Postgres with pg_textsearch. Get better search rankings with term frequency, IDF, and length normalization.
By Raja Rao DV
December 23rd, 2025
pg_textsearch brings BM25 ranking to enable hybrid search to Postgres. Build RAG systems with keyword precision and vector semantics in one database.
By Todd J. Green
October 23rd, 2025