Qdrant Raises $28M in Series A to Expand Open Source Vector Database for AI

Berlin-based company Qdrant has raised $28 million in a Series A funding round led by Spark Capital. Qdrant, which was founded in 2021, offers an open source vector search engine and database that is targeted at developers working in artificial intelligence (AI). The database is capable of drawing relationships between unstructured data, such as text, images, and audio, which is essential for generative AI. According to Gartner, unstructured data currently makes up around 90% of all new enterprise data and is growing at a much faster rate than structured data. Qdrant’s fundraising success reflects the growing demand for vector databases, with other companies in the field also securing significant amounts of funding. Qdrant plans to use the latest investment to build out its business team, as its workforce is currently mostly composed of engineers. The company recently developed a highly efficient compression technology called binary quantization, which can reduce memory consumption and enhance retrieval speeds. Qdrant’s open source credentials are seen as a major selling point, as they offer more control and flexibility to customers compared to proprietary or cloud-only solutions. The company’s open source vector search engine has attracted high-profile customers such as Deloitte, Accenture, and Elon Musk’s xAI, among others. Qdrant has also launched a managed on-premise edition, providing enterprises with the option to host the database internally and access premium features and support. Qdrant’s cloud edition is already available on Amazon Web Services and Google Cloud Platform, with Microsoft Azure support recently added. Overall, Qdrant’s successful funding round and growing customer base highlight the increasing importance of open source vector databases in the AI industry.