Managed Vector Database Enables Seamless Deployment From Data Center, to Cloud, to the Edge
BERLIN & NEW YORK–(BUSINESS WIRE)–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.
Vector databases have emerged as a critical component for building AI-based (and especially generative AI-based) applications. Qdrant Hybrid Cloud marks a major advancement in the field of vector search and enterprise AI, bringing vector search applications to the next level and redefining the standard for enterprise-grade vector search and AI applications. It provides a rich set of features for performance optimization and excels in handling billions of vectors with unmatched efficiency, scale, and memory safety.
With its innovative hybrid cloud offering — supported in any Kubernetes cloud environment and a growing number of platforms — Qdrant doubles down on its position as the vector database of choice for enterprise-grade AI applications. In addition to running on AWS, Google Cloud Platform and Azure, enterprises can run dedicated managed vector databases on Oracle Cloud Infrastructure (OCI), Red Hat OpenShift, Vultr, DigitalOcean, OVHcloud, Scaleway, STACKIT, Civo, and any other private or public infrastructure with Kubernetes support.
“Enterprises need to run their vector database applications in any environment with full control over their data, and Qdrant Hybrid Cloud is built to address exactly this,” said André Zayarni, CEO & Co-Founder of Qdrant. “With Hybrid Cloud, Qdrant takes the next step in enabling large enterprises to face complex challenges and better build and implement robust, next-gen AI applications while meeting strict risk and compliance standards.”
Qdrant Hybrid Cloud, whose innovative architecture ensures complete database isolation, allows customers to deploy a vector database in their chosen environment without sacrificing the benefits of a managed cloud service. It gives users and customers maximum control over their data and vector search workloads, enabling companies to unlock unprecedented opportunities to deliver personalized customer experiences in the era of AI while upholding privacy and data sovereignty. This strategic approach, rooted in Qdrant’s commitment to open-source principles, will foster a new level of trust and reliability as companies navigate the evolving enterprise AI landscape.
“Qdrant Hybrid Cloud makes Qdrant a game-changer in the vector database domain by enabling unmatched deployment flexibility, ultra-low latency, and guaranteed data privacy and sovereignty. This sets a new bar for enterprise-grade vector search and applications,” said Bastian Hofmann, Director of Enterprise Solutions at Qdrant.
Qdrant was recently named in the ROSS index by Runa Capital as one of the top trending open-source startups in 2023. The vector database market is on a trajectory for rapid growth, fueled by the integration of generative AI and retrieval-augmented generation (RAG) techniques that enhance large language models with external, proprietary data. This growth is integral to the expansion of the generative AI market, where RAG plays a significant role in driving innovation, customized user experiences, and application diversity.
To learn more about Qdrant Hybrid Cloud, please visit qdrant.tech/blog/hybrid-cloud.
About Qdrant:
Qdrant is the leading, high-performance, scalable, open-source vector database and search engine, essential for building the next generation of AI/ML applications. Qdrant is able to handle billions of vectors, supports the matching of semantically complex objects, and is implemented in Rust for performance, memory safety, and scalability.
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