PlanetScale has introduced general availability of vector support, allowing users to store vector data alongside relational MySQL data, streamlining application architecture. Following a successful public beta, substantial performance enhancements were made, including doubled query performance and eight-fold memory efficiency gains. This new functionality caters to modern applications like recommendation systems and semantic search. The implementation employs innovative algorithms, SPANN and SPFresh, for managing larger-than-RAM indexes, though integration into the MySQL Community remains unlikely.
PlanetScale’s recently launched vector support allows storing vector data with relational MySQL data, aiming to simplify database architecture by eliminating the need for separate vector databases.
The new vector capabilities enable direct support for recommendation systems, semantic search, and RAG workloads on a MySQL-compatible engine, providing enhanced functionality for modern applications.
With the introduction of vector search, PlanetScale doubled query performance and improved memory efficiency eight times, emphasizing robust performance across all data types.
Key differentiator of PlanetScale's vector support includes the ability to use indexes larger than RAM, enabled by SPANN and SPFresh algorithms from Microsoft Research.
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