Pg_textsearch – BM25 Ranking for Postgres

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Pg_textsearch – BM25 Ranking for Postgres is a business in show hn launch.

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I built pg_textsearch, a Postgres extension that brings proper BM25 ranking to full-text search. It's designed for AI/RAG workloads where search quality directly impacts LLM output.Postgres native ts_rank lacks corpus-aware signals (no IDF, no TF saturation, no length normalization). This causes mediocre documents to rank above excellent matches, which matters when your LLM depends on retrieval quality.Quick example: CREATE EXTENSION pg_textsearch; CREATE INDEX articles_idx ON articles USING bm25(content); SELECT title, content <@> to_bm25query('database performance', 'articles_idx') AS score FROM articles ORDER BY score LIMIT 10; Works seamlessly with pgvector or pgvectorscale for hybrid se

Pg_textsearch – BM25 Ranking for Postgres is positioned in show hn launch, a segment that rewards a clear, focused offering.

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Website: docs.tigerdata.com/use-timescale/latest/extensions/pg-textsearch