Qdrant

Qdrant is a vector database built in Rust with an emphasis on performance and efficiency. It is open source under Apache 2.0, which means you can run it on a laptop, in a container, or across a cluster without a licence conversation.

Technical strengths

• Rich filtering. A payload system with proper indexing lets you combine vector similarity with structured conditions without the recall loss naive post-filtering causes.
• Quantisation. Scalar, product, and binary quantisation cut memory use dramatically — often the difference between one server and five.
• Hybrid search with sparse vectors alongside dense ones.
• Multitenancy through payload-based partitioning within a single collection.
• Distributed mode with sharding and replication for horizontal scale.
• Fast in practice. Published benchmarks consistently place it near the top for queries per second at a given recall.

Deployment

Run it yourself with Docker or Kubernetes, or use Qdrant Cloud (managed, on AWS, GCP, or Azure) with a free tier. Client libraries cover Python, JavaScript, Rust, Go, Java, and .NET, and it integrates with the major agent frameworks.

A common default when you want production-grade vector search without a vendor dependency.