qdrant.io
Qdrant is an open-source vector database and search engine designed for efficient similarity search in AI applications.
About qdrant.io
Qdrant is an open-source, high-performance vector database built in Rust, offering fast and scalable similarity search for AI applications. Its intuitive API allows seamless integration with popular embedding models and frameworks, enabling use cases like matching, searching, and recommendations. Qdrant also features advanced scoring and reranking capabilities, making it ideal for complex AI-driven data analysis and retrieval tasks.
How to Use
Deploy Qdrant locally using Docker with the Quick Start Guide or via the GitHub repository. Convert embeddings or neural network outputs into applications for efficient matching, searching, and recommendation tasks.
Features
- Simple deployment and user-friendly interface
- Seamless integration with leading embedding frameworks
- Built in Rust for robustness and speed
- Supports large-scale, high-performance vector searches
- Scalable cloud-native architecture with high availability
- Cost-effective storage with compression options
Use Cases
- Anomaly detection and data pattern analysis
- Personalized recommendation engines
- Retrieval-augmented generation (RAG) for AI content
- Deep semantic similarity search
- AI agents for complex task execution
Best For
Pros
- Open-source and built in Rust for optimal performance
- Integrates smoothly with diverse embedding models
- Trusted by leading AI solutions worldwide
- Offers scalable, cloud-native deployment options
- Enables fast, accurate vector similarity searches
- Includes cost-efficient storage with compression
Cons
- Requires technical expertise for deployment and management
- Enterprise pricing details available only upon request
Pricing Plans
Choose the perfect plan. All plans include 24/7 support.