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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Meta Configuration of Package pgvectorscale

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