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Changelog — PlanetScale

Replica connections graph — PlanetScale Branch start maintenance webhook now available for Vitess enterprise customers — PlanetScale Deploy request UI updates — PlanetScale PostgreSQL CPU and I/O tracking — PlanetScale Branch start maintenance webhook — PlanetScale Cloudflare Workers integration — PlanetScale PlanetScale for Postgres is now Generally Available — PlanetScale PostgreSQL Schema Recommendations — PlanetScale Postgres maintenance windows — PlanetScale Support for 10 new Postgres extensions — PlanetScale 2025 PCI DSS reporting now available — PlanetScale AWS PrivateLink for Postgres — PlanetScale Google Cloud Provider support for Postgres databases — PlanetScale Insights: percent runtime — PlanetScale New region: AWS ca-central-1 (Montreal) — PlanetScale Postgres event triggers are now supported — PlanetScale New Postgres extension: pg_squeeze — PlanetScale Provisioned IOPS display for Metal clusters — PlanetScale Insights: max query latency graphs — PlanetScale Pinned databases update — PlanetScale New Postgres extensions: pg_cron and pg_partman_bgw — PlanetScale pscale shell now supports Postgres databases — PlanetScale Migration guides for Aurora, Neon, and Supabase — PlanetScale New pscale role commands for CLI — PlanetScale Postgres migration guides and scripts — PlanetScale Postgres role management — PlanetScale Expanded Postgres network-attached storage I/O configuration — PlanetScale 2025 SOC 1 Type 2 & SOC 2 Type 2 reports now available — PlanetScale Prometheus Metrics Additions: vstreamer events and errors — PlanetScale Postgres network-attached storage configuration — PlanetScale
PlanetScale vectors now supports quantization — PlanetScale
2024-11-20 · via Changelog — PlanetScale

PlanetScale vectors now supports quantization. Quantization is a form of vector compression that allows your vector indexes to consume less space.

This change brings support for product_quantization and fixed_quantization. You can configure these for your indexes by specifying them in the SECONDARY_ENGINE_ATTRIBUTE when creating your indexes. For example:

CREATE VECTOR INDEX embedding_index ON table_1(embedding)
  SECONDARY_ENGINE_ATTRIBUTE='{"type":"spann", "distance":"l2", "product_quantization":{"dimensions":96}}';
CREATE VECTOR INDEX embedding_index ON table_1(embedding)
  SECONDARY_ENGINE_ATTRIBUTE='{"type":"spann", "distance":"l2", "fixed_quantization":"bfloat16"}';

Learn more in our vectors documentation.