ParadeDB extends PostgreSQL with production-grade search capabilities that previously required deploying and maintaining a separate Elasticsearch or Solr cluster. The pg_search extension implements BM25 full-text ranking, phrase matching, fuzzy search, and faceted aggregations using a Rust-based indexing engine that runs as a native Postgres extension. Queries execute through standard SQL syntax, meaning existing application code and ORMs work without modification.
Hybrid search combines traditional BM25 keyword matching with vector similarity search in a single query, addressing the growing need for applications that blend exact text retrieval with semantic understanding. This eliminates architectures where teams pipe results between a vector database and a text search engine, reducing latency and complexity. The extension stores indexes alongside regular Postgres data, inheriting backup, replication, and failover infrastructure that teams have already built.
Backed by a 12 million dollar Series A with over 500,000 Docker deployments and 100,000+ extension installs, ParadeDB has established itself as the leading Postgres-native search solution. The AGPL-3.0 license governs the community edition with a managed cloud in development. Performance benchmarks show competitive query latency against standalone Elasticsearch, with the significant operational advantage of eliminating an entire infrastructure component from the stack.
