Qdrant has released version 1.20, introducing significant enhancements to its open-source vector database. This update integrates BM25 keyword ranking directly into the full-text index, eliminating the need for separate embedding models and pipelines for keyword search. The new version also features a code tokenizer for improved identifier matching, per-element indexes that accelerate nested filter operations, and two new TurboQuant data types (Turbo16 and Turbo8) for reduced vector storage with minimal recall impact. Security has been bolstered with default internal authentication for the peer gRPC port, and memory-tier optimizations for HNSW indexes are now available. AI
IMPACT Enhances retrieval capabilities for AI applications by integrating keyword search directly into vector databases.
RANK_REASON This is a product update for a vector database, not a frontier model release.
- Azure Blob Storage
- BM25
- Google Cloud Storage
- Hierarchical Navigable Small World graphs
- Qdrant
- Qdrant 1.20
- Turbo16
- Turbo8
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →