PostgreSQL continues to dominate the database landscape—over 84,000 companies rely on it as of 2025, and that number keeps growing.



Here's the thing: keyword search isn't going away. It remains fundamental for most applications. But here's where it gets interesting—Tiger Data recently open-sourced pg_textsearch, which brings BM25-ranked search capabilities directly into Postgres. This isn't just another search tool; it works seamlessly with pgvector to enable hybrid search workflows.

For developers building performant search layers, this combination changes the game. You get efficient full-text search powered by BM25 algorithms while maintaining vector similarity capabilities in the same database. No need to juggle multiple systems—everything lives in Postgres.
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alpha_leakervip
· 6h ago
No, no, pg_textsearch is really amazing. I finally don't have to mess around with that bunch of broken Elasticsearch stuff anymore.
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ThreeHornBlastsvip
· 11h ago
It's just about pushing search capabilities into Postgres; the real issue is that most people are still too lazy to optimize their queries...
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TokenVelocityTraumavip
· 11h ago
The PostgreSQL ecosystem is getting competitive again. Pairing pg_textsearch with pgvector allows for a one-stop solution, eliminating the need for multiple systems. Truly convenient.
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UnluckyValidatorvip
· 11h ago
The operation of pg_textsearch is interesting; BM25+pgvector directly eliminated a bunch of search solutions.
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AllTalkLongTradervip
· 11h ago
Wow, the combination of pg_textsearch + pgvector is really awesome. One library handles all search needs, no more juggling multiple systems.
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