Unveiling Milvus 2.4: Multi-vector Search, Sparse Vector, CAGRA Index, and More!

What this post added

Introduced multi-vector search allowing simultaneous search and reranking of different vector types within a collection, storing/querying multiple vectors per entity, and building reranking algorithms. Added Grouping Search for fields of types BOOL, INT, or VARCHAR, with an iterator-based implementation for efficiency. Introduced beta support for sparse vector embeddings, treating them on par with dense vectors and supporting Inner Product distance metric. Added support for the GPU-based CAGRA index for accelerated graph indexing. Enhanced metadata filtering with Regular Expression support and introduced a scalar inverted index.