Qdrant

What is Qdrant?

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. It blends vector similarity with custom logic using Score Boosting Reranker. Qdrant integrates with all leading embeddings and frameworks, turning embeddings or neural network encoders into full-fledged applications for matching, searching, recommending, and more.

How to use Qdrant?

Deploy Qdrant locally with Docker using the Quick Start Guide or the GitHub repository. Turn embeddings or neural network encoders into applications for matching, searching, and recommending.

Qdrant’s Core Features

High-performance vector search at scale Cloud-native scalability & high-availability Ease of use & simple deployment Cost efficiency with storage options Rust-powered reliability & performance Integrates with leading embeddings and frameworks

Qdrant’s Use Cases

• Advanced Search: Enables nuanced similarity searches and understanding semantics in depth.
• Recommendation Systems: Creates personalized recommendation systems with tailored suggestions.
• Retrieval Augmented Generation (RAG): Enhances the quality of AI-generated content.
• Data Analysis and Anomaly Detection: Identifies patterns and outliers in complex datasets.
• AI Agents: Allows them to handle complex tasks, adapt in real time, and drive smarter, data-driven outcomes.