Qdrant
Provides a high-performance, massive-scale vector database and search engine for AI applications.
About
Qdrant is a robust vector similarity search engine and database designed for the next generation of AI applications. It offers a production-ready service with a user-friendly API for storing, searching, and managing vectors alongside their associated payloads. Written in Rust for speed and reliability, Qdrant excels in extended filtering support, making it ideal for neural network or semantic-based matching, faceted search, and recommender systems. It is also available as a fully managed cloud service, Qdrant Cloud.
Key Features
- Comprehensive horizontal scaling with sharding and replication
- Support for hybrid search with sparse and dense vectors
- 24,060 GitHub stars
- Attach and filter any JSON payloads to vectors
- Vector quantization and on-disk storage for resource efficiency
- Optimized query execution with payload indexes and SIMD hardware acceleration
Use Cases
- Extreme classification and product categorization
- Similar image search and visual discovery
- Semantic text search and information retrieval
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