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This is a beta feature available in versions 0.25.0 and above.
Today, most Postgres users rely on the pgvector extension for similarity (i.e. vector) search. pgvector works well for many use cases, but has a few limitations:
  • Filtering Performance: Its indexes are separate from the ParadeDB index, so performance suffers when composing vector search with text search and other filters.
  • Memory Constraints: Index build times balloon when the entire index does not fit in memory, preventing pgvector from scaling to large datasets.
  • Index Quality Under Updates: Indexes can degrade over time under update-heavy workloads.
The ParadeDB index supports pgvector’s vector type and is designed to solve these limitations. Vectors are indexed with a SPANN-style index, the state-of-the-art approach for billion-scale vector search.