pg_textsearch

Very exciting! Congrats on the release, this will be a huge benefit to all folks building RAG/rerank systems on top of Postgres. Looking forward to testing it out myself.

I've been doing some RAG prototypes with hybrid search using pg_textsearch plus pgvector and have been very pleased with the results. Happy to see a 1.0 release!

This is pretty much my case right now. BM25 is so useful in many cases and having with with postgres is neat!

we have been using pg_textsearch in production for a few weeks now, and it's been fairly stable and super speedy. we used to use paradedb (aka pg_search -- it's quite annoying…

This is really cool to see! I've been using BM25+sqlite-vec for contextual search projects for a little while, it's a great performance addition.

Nice work. pg_search has been on my radar for a while, having BM25 natively in Postgres instead of bolting on Elasticsearch is a huge DX win. Curious about the index build time…

“Just use Postgres” greybeards right again. Looking forward to giving this a go soon

This is really cool. I've built things on PostgreSQL ts_vector() FTS in the past which works well but doesn't have whole-index ranking algorithms so can't do BM25. It's a bit…

While we’re talking about filtering — is there a way to set a WHERE clause when you’re setting up the index? I’ve been working on this a lot recently for a hybrid vector search…

Noticed it's only pg17, is that some hard dependency? Also why did you choose C for this and not rust, any specific reason? I see pgvectorscale is built on rust

you need to explain claude code that PG18 is out already ;)

The "term positions" caveat seems like a major limitation for human oriented searches of logs or products or whatever. I don't see it mentioned in what's next, will you address…

What architectural decisions enabled pg_textsearch to outperform Tantivy/ParadeDB by 4.7×, especially given Tantivy’s reputation for speed?

vibes

VERY excited about this, literally just looking to build hybrid search using Postgres FTS. When will this be available on Supabase?

When is this available on AWS in Aurora? Anyone from AWS here, add it pronto

Please oh please let GCP add this to the supported managed Postgres extensions...

And Azure Flexible server please

I hope someone from Neon is watching this thread, definitely want to play with this asap

CJK tokenization is one of those things that looks simple until you actually try it. Japanese alone needs morphological analysis (MeCab etc.) because there are no word boundaries…

Interesting timing — we've been tackling similar full-text search challenges over Japanese financial filings (roughly 9M+ sections from annual reports). The tokenization problem…

Partitions would be one option, and we've got pretty robust partitioned table support in the extension. (Timescaledb uses partitioning for hypertables, so we had to front-load…

Impressive benchmarks. How does the BM25 implementation handle high-frequency updates (writes) while maintaining search latency? Usually, there's a trade-off between ingest speed…

Impressive benchmarks. How does the BM25 implementation handle high-frequency updates (writes) while maintaining search latency? Usually, there's a trade-off between ingest speed…

Nice work. pg_search has been on my radar for a while, having BM25 natively in Postgres instead of bolting on Elasticsearch is a huge DX win. Curious about the index build time…

While we’re talking about filtering — is there a way to set a WHERE clause when you’re setting up the index? I’ve been working on this a lot recently for a hybrid vector search…

Nice work. pg_search has been on my radar for a while, having BM25 natively in Postgres instead of bolting on Elasticsearch is a huge DX win. Curious about the index build time…

we have been using pg_textsearch in production for a few weeks now, and it's been fairly stable and super speedy. we used to use paradedb (aka pg_search -- it's quite annoying…

I've been doing some RAG prototypes with hybrid search using pg_textsearch plus pgvector and have been very pleased with the results. Happy to see a 1.0 release!

Nice work. pg_search has been on my radar for a while, having BM25 natively in Postgres instead of bolting on Elasticsearch is a huge DX win. Curious about the index build time…

Last summer we faced a conundrum at my company, Tiger Data, a Postgres cloud vendor whose main business is in timeseries data. We were trying to grow our business towards…