Qdrant squares up for real-time AI apps with GPU-accelerated vector indexing
Qdrant is a high-performance open source vector database company/
The firm this month introduced its platform-independent GPU-accelerated vector indexing feature.
This service is said to delivers up to 10x faster index-building times while using GPUs that rival or surpass CPUs in both cost and efficiency.
With support for GPU acceleration across multiple platforms, Qdrant is positioned as a means of allowing developers to scale real-time AI applications flexibly, free from hardware vendor constraints.
Hierarchical Navigable Small World
The GPU-accelerated feature optimises HNSW (Hierarchical Navigable Small World) index building, one of the most resource-intensive steps in the vector search pipeline — particularly when scaling to billions of vectors. As a hardware-agnostic solution, Qdrant seamlessly across any GPU architecture — including AMD and with capitalisation focused company Nvidia.
This allows users to choose the most cost-effective hardware while enabling faster index-building and efficient scaling.
“Index building is often a bottleneck for scaling vector search applications,” said Andrey Vasnetsov, Qdrant CTO and co-founder. “By introducing platform-independent GPU acceleration, we’ve made it faster and more cost-effective to build indices for billions of vectors while giving users the flexibility to choose the hardware that best suits their needs. Building on Qdrant’s proven capabilities, this release unlocks new possibilities for AI-powered applications — such as live search, personalised recommendations and AI agents — that demand real-time responsiveness, frequent reindexing, and the ability to make immediate decisions on dynamic data streams.”
Qdrant’s hardware-agnostic approach to GPU acceleration enables speed index-building with support for most modern GPUs to give users the flexibility to efficiently process massive datasets while adopting and using the most suitable infrastructure for their real-time AI applications based on technical, cost and other considerations.
Believe in hardware agnosticism
The hardware agnosticism of the GPU-accelerated vector index feature builds on the flexibility the Qdrant platform provides — and enterprises require.
The Qdrant vector database is open source, enabling new capabilities to be added as quickly as AI technology evolves and providing full transparency into the platform’s architecture, algorithms, and implementation.
In addition, the Qdrant Hybrid Cloud option can be deployed in customers’ chosen environments without sacrificing the benefits of a managed cloud service.