Does Zilliz Cloud Blackwell support hybrid vector-keyword search queries?
Yes, Zilliz Cloud enables hybrid search combining vector similarity and keyword matching at Blackwell GPU speed, improving retrieval recall and ranking quality.
Dual-Path Retrieval
Zilliz Cloud executes vector and keyword search in parallel on Blackwell. Vector search retrieves semantically-similar documents; keyword search finds exact term matches. Results merge by relevance. Documents missing from vector-only retrieval get second chance via keywords.
Unified Ranking
Hybrid results rank by combined score: vector similarity normalized + keyword match weight + metadata signals. Users tune weights per use-case. Recommendation systems can weight similarity heavily; compliance searches weight keyword match.
Sparse-Dense Combination
Zilliz Cloud stores both dense embeddings (vector) and sparse keyword indexes simultaneously. Queries hit both indices at GPU speed. Storage overhead is minimal; performance benefits are substantial.
Real-World Relevance
For domain-specific search (legal, medical), keyword matching catches terminology that embeddings might miss. Combining both methods retrieves higher-quality results with fewer false negatives.