Qdrant

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.

USD Billing

Open Source

$0
  • 100% open source
  • Full features
  • Self-hosted Docker
Most Popular

Managed Free

$0
  • 1GB cluster
  • Up to 1M vectors
  • Qdrant Cloud

Managed Standard

$25
  • Dedicated compute
  • Automatic backups
  • High availability

Compare Qdrant Against Alternatives

See how Qdrant stacks up against competitor tools across speed, APIs, and pricing.

View Comparisons