Qdrant Receives Industry Honors for Innovation in AI and Vector Search
Qdrant, the high-performance, open-source vector database, today announced that it received two esteemed industry accolades. CB Insights named Qdrant to its ninth annual AI 100 list, honoring the 100 most promising private artificial intelligence companies globally. In addition, Qdrant won a 2025 AI TechAward in the "Data Storage and Access" category, to be presented at the upcoming AI DevSummit 2025 in San Francisco, CA.
Qdrant Expands Enterprise Capabilities with New Cloud Features, Strengthening AI Workloads for Large-Scale Deployments
As AI adoption accelerates, enterprises are facing new challenges in scaling, securing, and managing high-performance AI applications. Today, Qdrant, the high-performance, open-source vector database, is introducing new enterprise capabilities in Qdrant Cloud that are designed to remove operational bottlenecks and empower large-scale AI deployments. The latest updates include single sign-on (SSO), cloud role-based access control (RBAC), granular database API keys for granular RBAC, advanced monitoring and observability with Prometheus/OpenMetrics to connect external monitoring systems, and a cloud API for seamless automation.
Qdrant Launches the First Platform-Independent GPU-Accelerated Vector Indexing for Real-Time AI Applications
Qdrant, the leading high-performance open-source vector database, today introduced its platform-independent GPU-accelerated vector indexing. This new feature delivers up to 10x faster index-building times while leveraging cost-effective GPUs that rival or surpass CPUs in both cost and efficiency. With support for GPU acceleration across multiple platforms, Qdrant empowers developers to scale real-time AI applications flexibly and free from hardware vendor constraints.
Qdrant Launches Groundbreaking Pure Vector-Based Hybrid Search, Setting Higher Standards for RAG and AI Applications
Qdrant, the leading high-performance open-source vector database, today announced the launch of BM42, a pure vector-based hybrid search approach that delivers more accurate and efficient retrieval for modern retrieval-augmented generation (RAG) applications. The BM42 search algorithm marks a significant step forward beyond traditional text-based search for RAG and AI applications.
Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
Qdrant, the leading high-performance, open-source vector database, today announced the availability of its new Qdrant Hybrid Cloud, the industry’s first dedicated vector database to be offered in a managed hybrid cloud model. With its run-anywhere self-service solution, Qdrant enables businesses to efficiently deploy and manage vector databases across any cloud provider, on-premise, or edge location. This ensures performance, security, and cost efficiency for AI-driven applications, as well as the ability for organizations to control and protect where and how sensitive data is used.
Qdrant Raises $28M to Advance Massive-Scale AI Applications
Qdrant, the leading high-performance, open-source vector database, today announced the successful completion of its Series A funding round, securing a $28M investment led by Spark Capital, with participation from existing investors Unusual Ventures and 42CAP.
