Tiger Data is the company behind TimescaleDB, a popular time-series database extension for PostgreSQL. The company builds tools that enhance PostgreSQL for time-series data, real-time analytics, and AI applications.
They have now open-sourced pg_textsearch, their PostgreSQL extension that brings modern search capabilities to the database. Let's check it out! 😃
pg_textsearch Goes Open
Tiger Data has released pg_textsearch under The PostgreSQL License on GitHub. The extension was previously available only on Tiger Cloud, their managed database platform.
Announcing this move, Michael Freedman, the CTO of Tiger Data, stated that:
If you care about fast, relevance-ranked keyword search without leaving Postgres – or hybrid retrieval by combining pg_textsearch with pgvector/pgvectorscale – this is for you.
The extension lets developers run BM25 relevance-ranked keyword searches directly in PostgreSQL without them needing to set up an external search system like Elasticsearch.
BM25 is the industry-standard ranking algorithm behind modern search engines. With pg_textsearch, you can now run it inside Postgres for relevance-ranked text search. pg_textsearch pairs naturally with pgvector to support keyword + semantic search in a single database.
Some additional details can be found in this blog post.
Todd J. Green
Some key features of pg_textsearch include:
- Support for 29+ languages.
- Works with partitioned tables.
- Simple SQL syntax with the
<@>operator. - Memtable architecture for efficient indexing.
- BM25 ranking with configurable ranking parameters (k1, b).
Tiger Data positions this as the first step toward their Postgres Search Stack, aimed at Postgres developers, infrastructure engineers, and AI app builders. The stack will combine keyword search via pg_textsearch with vector search through pgvector and pgvectorscale, giving teams a complete search solution inside PostgreSQL.
Suggested Read 📖: Is SysAdmin Still a Good Career Choice in 2026?
Abhishek Prakash
