🗂️ Navigation

Qdrant

Vector Database for the next generation of AI.

Visit Website →

Overview

Qdrant is a vector database and vector similarity search engine written in Rust. It provides a production-ready service with a convenient API to store, search, and manage points-vectors with an additional payload. Qdrant is designed to provide extensive filtering support, making it a good choice for neural network or semantic-based matching, faceted search, and other applications.

✨ Key Features

  • Open-source
  • Written in Rust for performance and safety
  • Advanced filtering capabilities
  • Payload indexing
  • Horizontal scaling

🎯 Key Differentiators

  • Written in Rust
  • Advanced filtering
  • Performance and safety

Unique Value: Qdrant offers a robust and performant open-source vector database with powerful filtering capabilities, ideal for building advanced AI applications.

🎯 Use Cases (5)

Semantic search Recommendation systems Anomaly detection Similarity matching Retrieval-Augmented Generation (RAG)

✅ Best For

  • Building search engines with complex filtering requirements
  • Powering recommendation systems with real-time updates

💡 Check With Vendor

Verify these considerations match your specific requirements:

  • Storing large amounts of non-vector data

🏆 Alternatives

Pinecone Weaviate Milvus

Qdrant's use of Rust and its focus on advanced filtering differentiate it from other open-source and managed vector databases.

💻 Platforms

Self-hosted API

✅ Offline Mode Available

🔌 Integrations

LangChain LlamaIndex OpenAI Hugging Face

🔒 Compliance & Security

✓ GDPR ✓ SSO

💰 Pricing

Contact for pricing
Free Tier Available

Free tier: Open-source version is free to self-host.

Visit Qdrant Website →