Qdrant was founded in 2021 by Andre Zayarni and Andrey Vasnetsov in Berlin, Germany. The company builds an open-source vector database written entirely in Rust, prioritizing performance, memory efficiency, and reliability for production AI workloads.
Qdrant raised $12 million in a Series A led by Spark Capital in 2023, with participation from unusual ventures. The choice of Rust as the implementation language gives Qdrant strong performance characteristics and memory safety guarantees that matter in production environments.
The engine supports advanced filtering alongside vector search, letting users combine semantic similarity queries with traditional attribute-based filters in a single request. This hybrid approach is essential for real-world applications where you need results that are both semantically relevant and match specific business criteria.
Qdrant offers both self-hosted deployment and a managed cloud service. Its API supports gRPC and REST, with client libraries for Python, TypeScript, Rust, Go, and Java. The project has garnered significant traction on GitHub, with a growing community of contributors.
Companies use Qdrant for recommendation systems, anomaly detection, image search, and RAG applications. Its low memory footprint and ability to handle quantized vectors make it attractive for teams running on constrained infrastructure or processing very large datasets. The team has grown to around 50 employees.
