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server:database:postgresql
pgvectorscale
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Meta Configuration of Package pgvectorscale
<package name="pgvectorscale" project="server:database:postgresql"> <title>A complement to pgvector for high performance, cost efficient vector search on large workloads</title> <description>pgvectorscale complements pgvector, the open-source vector data extension for PostgreSQL, and introduces the following key innovations for pgvector data: - A new index type called StreamingDiskANN, inspired by the DiskANN algorithm, based on research from Microsoft. - Statistical Binary Quantization: developed by Timescale researchers, This compression method improves on standard Binary Quantization. On a benchmark dataset of 50 million Cohere embeddings with 768 dimensions each, PostgreSQL with pgvector and pgvectorscale achieves 28x lower p95 latency and 16x higher query throughput compared to Pinecone's storage optimized (s1) index for approximate nearest neighbor queries at 99% recall, all at 75% less cost when self-hosted on AWS EC2.</description> <url>https://github.com/timescale/pgvectorscale</url> </package>
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