Qdrant, a vector database and similarity search engine, is revolutionizing AI applications with its advanced and high-performance vector similarity search technology. Trusted by leading companies, Qdrant stands out for its top-notch performance, scalability, user-friendly interface, and flexible cost-saving options.
Why Choose Qdrant?
- Easy Integration with API: Qdrant provides a straightforward OpenAPI v3 specification, making it easy to generate client libraries in various programming languages.
- Swift and Accurate Searches: Employing a customized version of the HNSW algorithm, Qdrant ensures state-of-the-art speed without compromising accuracy in Approximate Nearest Neighbor Search.
- Filterable and Rich Data Support: Qdrant not only stores but allows filtering based on additional payload associated with vectors. Supporting diverse data types and query conditions, it facilitates the creation of custom business logic on top of similarity matching.
- Cloud-Native and Efficient: Qdrant is designed to be cloud-native, scaling horizontally to accommodate varying data sizes. Developed in Rust language, it efficiently utilizes resources, with hardware-aware builds available for enterprises.