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timescale
pg_textsearch
C2025–2026
timescale / pg_textsearch

pg_textsearch

PostgreSQL extension for BM25 relevance-ranked full-text search. Postgres OSS licensed.

Data & DatabasesSearch & Information Retrieval
Explore on GitHubRead Hacker News discussions
6Distinct people
14Mentions
0Explicit recommenders
4.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

PostgreSQL extension for BM25 relevance-ranked full-text search. Postgres OSS licensed.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month14 dated mentions

Observed mentions: 2025-12-15 18:15:55 UTC to 2026-09-19 15:32:46 UTC.

024682025-12-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 8 mentions; 7 submissions, 1 commentsDec 20252026-01-01 00:00:00 UTC to 2026-02-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-02-01 00:00:00 UTC to 2026-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-03-01 00:00:00 UTC to 2026-04-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2026-04-01 00:00:00 UTC to 2026-05-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsApr 20262026-05-01 00:00:00 UTC to 2026-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-06-01 00:00:00 UTC to 2026-07-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-07-01 00:00:00 UTC to 2026-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-08-01 00:00:00 UTC to 2026-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-09-01 00:00:00 UTC to 2026-10-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsSep 2026

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Dec 20252025-12-01 00:00:00 UTC2026-01-01 00:00:00 UTC871
Jan 20262026-01-01 00:00:00 UTC2026-02-01 00:00:00 UTC101
Feb 20262026-02-01 00:00:00 UTC2026-03-01 00:00:00 UTC000
Mar 20262026-03-01 00:00:00 UTC2026-04-01 00:00:00 UTC211
Apr 20262026-04-01 00:00:00 UTC2026-05-01 00:00:00 UTC101
May 20262026-05-01 00:00:00 UTC2026-06-01 00:00:00 UTC000
Jun 20262026-06-01 00:00:00 UTC2026-07-01 00:00:00 UTC101
Jul 20262026-07-01 00:00:00 UTC2026-08-01 00:00:00 UTC000
Aug 20262026-08-01 00:00:00 UTC2026-09-01 00:00:00 UTC000
Sep 20262026-09-01 00:00:00 UTC2026-10-01 00:00:00 UTC101

What Hacker News says

14 sources
andrenotgiant·Sep 19, 2026
I think what we're seeing with every database company providing new full-text search capabilities is an example of AI coding productivity showing up in the real world. It started with paradeDB and pg_search https://www.paradedb.com/blog/introducing-search Timescale has pg_textsearch https://github.com/timescale/pg_textsearch Neon and Databricks have Lakebase Search https://docs.databricks.com/aws/en/oltp/projects/lakebase-se... Now PlanetScale. AFAIK all of these are implementations of the BM25 algorithm. You can just tell an agent to read about BM25 and implement it in your system of choice. Cool to see. Seems like there's still a lot of juice to be squeezed out of how it's architected and integrated into each system, but you can't help but wonder if this will lead to aggressive commodification
In Tin: full-text search for Postgres
tjgreen·Mar 31, 2026Submission

Show HN: Postgres extension for BM25 relevance-ranked full-text search

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 emerging AI-centric workloads and wanted to provide a state-of-the-art hybrid search stack in Postgres. We'd already built pgvectorscale in house with the goal of scaling semantic search beyond pgvector's main memory limitations. We just needed a scalable ranked keyword search solution too. The problem: core Postgres doesn't provide this; the leading Postgres BM25 extension, ParadeDB, is guarded behind AGPL; developing our own extension appeared daunting. We'd need a small team of sharp engineers and 6-12 months, I figured. And we'd probably still fall short of the performance of a mature system like Parade/Tantivy. Or would we? I'd be experimenting long enough wit
Read the rest
h AI-boosted development at that point to realize that with the latest tools (Claude Code + Opus) and an experienced hand (I've been working in database systems internals for 25 years now), the old time estimates pretty much go out the window. I told our CTO I thought I could solo the project in one quarter. This raised some eyebrows. It did take a little more time than that (two quarters), and we got some real help from the community (amazing!) after open-sourcing the pre-release. But I'm thrilled/exhausted today to share that pg_textsearch v1.0 is freely available via open source (Postgres license), on Tiger Data cloud, and hopefully soon, a hyperscalar near you: https://github.com/timescale/pg_textsearch In the blog post accompanying the release, I overview the architecture and present benchmark results using MS-MARCO. To my surprise, we were not only able to meet Parade/Tantivy's query performance, but exceed it substantially, measuring a 4.7x advantage on query throughput at scale: https://www.tigerdata.com/blog/pg-textsearch-bm25-full-text-... It's exciting (and, to be honest, a little unnerving) to see a field I've spent so much time toiling in change so quickly in ways that enable us to be more ambitious in our technical objectives. Technical moats are moats no longer. The benchmark scripts and methodology are available in the github repo. Happy to answer any questions in the thread. Thanks, TJ (tj@tigerdata.com)
203 points · Open discussion

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