Open source vector database startup Qdrant raises $28M

Qdrant, a Berlin-based company, has raised $28 million in a Series A funding round led by Spark Capital to capitalize on the growing importance of unstructured data in the AI revolution. The company offers an open source vector search engine and database, which is essential for processing unstructured data in real-time AI applications. The funding will be used to expand the business team, develop new technologies, and offer managed services.

Binary quantization (BQ) is a new compression technology launched by Qdrant, claiming to reduce memory consumption by up to 32 times and improve retrieval speeds by 40 times. The technology aims to simplify the comparison of vectors, particularly benefiting AI models such as OpenAI’s and Cohere’s. Qdrant has attracted high-profile clients, including Deloitte, Accenture, and X (formerly Twitter), for real-time data processing.

Qdrant emphasizes its open source credentials as a major selling point, offering customers more control over their data and the flexibility to switch between deployment options. The company has recently released its managed “on-premise” edition, providing enterprises with the option to host everything internally while accessing premium features and support. Additionally, Qdrant’s cloud edition is now available on Microsoft Azure, in addition to existing support for AWS and Google Cloud Platform.