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Qdrant
Overview :
Qdrant is an open-source vector search database and search engine, written in Rust. It offers rapid and scalable vector similarity search services, accompanied by convenient APIs. Qdrant can integrate with any system and serves as the foundation for advanced and high-performance vector similarity search technology in the next generation of AI applications. It is a cloud-native vector database, capable of horizontal scaling, resource-efficient, and fully developed using the Rust programming language. Qdrant can address various business scenarios such as recommendation systems, semantic search, similar product discovery, fraud detection systems, and talent matching.
Target Users :
["Recommender System","Semantic Search","Similar Product Discovery","Fraud Detection System","Talent Matching"]
Use Cases
Real-time update of vectors based on user behavior to achieve personalized recommendations
Integration with deep learning models to provide semantic similarity search services
Search for similar products through product feature vectors
Detect anomalous transaction behaviors using account feature vectors
Features
User-friendly API
Fast and accurate search
Supports filtered search results
Supports multiple rich data types
Distributed deployment
Resource utilization efficient
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