The open-source vector similarity search engine and database written in Rust.
Technical Overview & Architecture
Qdrant is an open-source vector search database engineered in Rust for high-throughput, low-latency AI applications. It features advanced payload filtering integrated directly into its custom HNSW graph traversal, preventing recall degradation under strict metadata constraints. Qdrant supports comprehensive vector quantization (Scalar, Product, and Binary Quantization) and memory-mapped files (mmap) for storing billions of vectors on cost-effective SSD storage, with native support for multi-vector search and sparse-dense hybrid retrieval.
Pricing Breakdown
Transparent tiers and feature allotments for engineering teams.
Open Source
- 100% open source
- Full features
- Self-hosted Docker
Managed Standard
- Dedicated compute
- Automatic backups
- High availability
Compare Qdrant Against Alternatives
See how Qdrant stacks up against competitor tools across speed, APIs, and pricing.