Advanced vector similarity search for AI applications.

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Last commit1 week ago

License:

Apache-2.0

Languages:

Rust
Python
Shell
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Qdrant is a high-performance, open-source vector database designed to handle high-dimensional vectors for next-generation AI applications. It offers advanced vector similarity search technology, enabling powerful and scalable AI solutions, from recommendation systems to anomaly detection and beyond. Available both on-premises and in the cloud, Qdrant provides robust, reliable, and efficient vector search capabilities tailored for diverse use cases.

  • Cloud-Native Scalability & High-Availability: Enterprise-grade managed cloud with vertical and horizontal scaling, ensuring zero-downtime upgrades.
  • Ease of Use & Simple Deployment: Quick deployment in any environment with Docker and a lean API for easy integration, ideal for local testing.
  • Cost Efficiency with Storage Options: Reduce memory usage with built-in compression options and offload data to disk.
  • Rust-Powered Reliability & Performance: Built in Rust for unmatched speed and reliability, capable of processing billions of vectors.
  • Advanced Search: Process high-dimensional data with nuanced similarity searches and multimodal data handling.
  • Recommendation Systems: Create personalized recommendation systems with flexible API options for tailored suggestions.
  • Retrieval Augmented Generation (RAG): Enhance AI-generated content quality with efficient nearest neighbor search and payload filtering.
  • Data Analysis and Anomaly Detection: Identify patterns and outliers in complex datasets for robust, real-time anomaly detection.

Qdrant empowers developers and businesses to leverage the power of vectors to build advanced, high-performance AI applications. With its comprehensive feature set and flexible deployment options, Qdrant is a reliable solution for diverse AI-driven use cases.

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