Qdrant is an Open-Source Vector Database and Vector Search Engine written in Rust. It provides fast and scalable vector similarity search service with convenient API.
Cloud-Native Scalability
Enterprise-grade managed cloud with vertical and horizontal scaling and zero-downtime upgrades.
Ease of Use & Simple Deployment
Quick deployment in any environment with Docker and a lean API for easy integration.
Cost Efficiency with Storage Options
Dramatically reduce memory usage with built-in compression options and offload data to disk.
Rust-Powered Reliability & Performance
Purpose-built in Rust for unmatched speed and reliability when processing billions of vectors.
Qdrant is an open-source vector database and similarity search engine designed to handle high-dimensional vectors, enabling advanced AI applications at massive scale. It excels in processing complex data, allowing for nuanced similarity searches and understanding of semantics. Qdrant powers various AI solutions, offering a robust infrastructure for developers and enterprises to deploy high-performance applications easily.
Supports multimodal data, features a Recommendation API, and includes tools for data analysis and anomaly detection. Built-in compression options and quantization capabilities enhance storage efficiency.
Advanced Search for nuanced similarity searches in high-dimensional data
Personalized Recommendation Systems for tailored suggestions
Data Analysis and Anomaly Detection to identify patterns and outliers
Qdrant is an open-source vector database designed for high-performance similarity search and AI applications.
You can deploy Qdrant locally using Docker with a simple command and a quick start guide.
Qdrant is ideal for advanced search, recommendation systems, retrieval-augmented generation, and anomaly detection.
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