v.25.8New Feature
Vector similarity index now supports binary quantization
The vector similarity index now supports binary quantization. Binary quantization significantly reduces the memory consumption and speeds up the process of building a vector index (due to faster distance calculation). Also, the existing settingvector_search_postfilter_multiplierwas made obsolete and replaced by a more general setting :vector_search_index_fetch_multiplier. #85024 (Shankar Iyer).
Why it matters
Binary quantization reduces the memory consumption of vector similarity indexes and accelerates the building process by enabling faster distance calculations. This improvement optimizes resource utilization and query performance when working with vector data.How to use it
Users can take advantage of binary quantization by enabling the updated vector similarity index settings. The previous settingvector_search_postfilter_multiplier is now obsolete and replaced by vector_search_index_fetch_multiplier, which can be configured to control index fetching behavior.