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pg_bm25: Elastic-Quality Full Text Search Inside Postgres - ParadeDB

pg_bm25 is named after BM25, the algorithm used by modern search engines to calculate the relevance scores of search results

pg_bm25 aims to bridge the gap between the native capabilities of Postgres’ full text search and those of a specialized search engine like ElasticSearch. The goal is to eliminate the need to bring a cumbersome service like ElasticSearch into the data stack.

Built on top of Tantivy, a Rust-based alternative to the Apache Lucene search library

Support for fuzzy search, aggregations, highlighting, and relevance tuning

Relevance scoring uses BM25, the same algorithm used by ElasticSearch Real-time search — new data is immediately searchable without manual reindexing