Qdrant
Vector Database for the next generation of AI applications.
Overview
Qdrant is a high-performance vector similarity search engine and vector database. It is written in Rust, which provides memory safety and performance benefits. Qdrant is designed to be a reliable and efficient storage backend for vectors in RAG applications, offering advanced filtering capabilities and deployment flexibility with options for self-hosting, Kubernetes, and a managed cloud.
✨ Key Features
- Open source
- High-performance search written in Rust
- Advanced filtering with payload-based conditions
- Horizontal scaling
- On-disk storage for large datasets
- Managed cloud offering
🎯 Key Differentiators
- Written in Rust for performance and memory safety
- Advanced and flexible filtering capabilities
- Focus on reliability and production readiness
Unique Value: Delivers a high-performance, reliable, and feature-rich open-source vector database that gives developers the tools to build advanced AI applications with complex filtering requirements.
🎯 Use Cases (5)
✅ Best For
- E-commerce product matching
- Scientific literature search
- Duplicate detection
💡 Check With Vendor
Verify these considerations match your specific requirements:
- Users who need a completely hands-off, serverless experience
🏆 Alternatives
Qdrant's use of Rust and its focus on advanced filtering give it a performance and reliability edge for specific use cases compared to other vector databases written in different languages.
💻 Platforms
✅ Offline Mode Available
🔌 Integrations
🛟 Support Options
- ✓ Email Support
- ✓ Live Chat
- ✓ Dedicated Support (Enterprise tier)
🔒 Compliance & Security
💰 Pricing
✓ 14-day free trial
Free tier: Open source is free. Qdrant Cloud has a free tier.
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