Qdrant releases version 1.18 with TurboQuant
The update introduces a new quantization method, memory monitoring, and support for adding or removing named vectors.
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Open-source vector search engine
qdrant.techLast updated
In short: Qdrant raised $78M in total funding, launched version 1.18 with TurboQuant, and expanded its enterprise capabilities through a new Hybrid Cloud.
The update introduces a new quantization method, memory monitoring, and support for adding or removing named vectors.
Qdrant Edge enables on-device vector retrieval for sensor data, processing locally without cloud or latency. Ideal for IoT, robotics, and limited connectivity.
Sentinel detects misinformation by semantically searching news contradictions using Qdrant Cloud. It won first in Qdrant Challenge and placed top 10 overall.
These include GPU-accelerated indexing, Multi-AZ for 99.95% SLA, and audit logging for compliance. All are now available in Qdrant Cloud.
Funding Fuels Expansion of Qdrant’s Open-Source Vector Database, Enhancing Scalability and Efficiency for Next-Gen AI Use Cases. BERLIN--(BUSINESS WIRE)--Qdrant, the leading high-performance, open-source vector database...
Qdrant is packaging its open-source vector database tech into its new Hybrid Cloud, a managed service deployable into any environment -- cloud, on-premises or edge...
Qdrant, the leading provider of high-performance, composable vector search, today announced three enterprise capabilities for Qdrant Cloud: GPU-accelerated indexing, Multi-AZ clusters, and audit ...
This is how we configured Qdrant with tiered storage, aggressive quantization, and on-disk HNSW to handle billion-scale collections at 20% of the cost while maintaining...
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