A production-grade vector database with genuinely fast filtered search - the upgrade path once a prototype RAG app needs to handle real traffic and complex queries.
Where qdrant fits, based on its real tags and topics.
git clone https://github.com/qdrant/qdrant.gitSee the repository's README for language-specific setup steps.
Vector Search Engine for the next generation of AI applications
**Qdrant** (read: _quadrant_) is a vector similarity search engine and vector database. It provides a production-ready service with a convenient API to store, search, and manage points—vectors with an additional payload. Qdrant is tailored for extended filtering support, making it useful for all sorts of neural-network or semantic-based matching, faceted search, and other applications.
Qdrant is written in Rust 🦀, which makes it fast and reliable even under high load. See benchmarks.
Category: 🛢️ Databases
Difficulty: Intermediate
Part of: Database Essentials
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