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cutting edge innovation
powered by
Faster than IVFFlat
QUERY EXECUTION TIME (MS) AT 99% RECALL
13.2MS
262.3ms
HNSW
IVFFLAT
HNSW indexes bring 20x the speed for 99% accuracy to graph-based approximate nearest neighbor search in your Postgres database.
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Fully open-source
Uses HNSW
Scales to
Rows
get started
Store vector embeddings and perform similarity search
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Store embeddings and perform vector similarity search in Postgres with pgvector
benefits
Use the power of HNSW indexes to unlock new levels of efficiency in high-dimensional vector similarity search in Postgres.
pg_embedding is open-source and actively maintained by a team of Postgres committers at Neon.
pg_embedding supports HNSW indexes for fast and scalable vector similarity search.
Grow your vector stores without impacting search performance.
Easily switch to pg_embedding in your Postgres and LangChain projects.
