Qdrant - Vector Database

Qdrant is a leading open-source vector database and similarity search engine designed to handle high-dimensional vectors, making it ideal for performance-intensive and massive-scale AI applications. It powers the next generation of AI applications with its advanced, open-source vector similarity search technology.

Key Features

• Cloud-Native Scalability & High-Availability: Qdrant offers enterprise-grade managed cloud services with vertical and horizontal scaling capabilities, ensuring zero-downtime upgrades.
• Ease of Use & Simple Deployment: Deploy Qdrant quickly in any environment using Docker and a lean API, perfect for local testing and integration.
• Cost Efficiency with Storage Options: Reduce memory usage significantly with built-in compression options and offload data to disk.
• Rust-Powered Reliability & Performance: Built in Rust, Qdrant provides unmatched speed and reliability, even when processing billions of vectors.

Use Cases

• Advanced Search: Elevate applications with nuanced similarity searches and deep semantic understanding, especially for multimodal data.
• Recommendation Systems: Create personalized recommendation systems with tailored suggestions using Qdrant’s Recommendation API.
• Retrieval Augmented Generation (RAG): Enhance AI-generated content by leveraging efficient nearest neighbor search and payload filtering.
• Data Analysis and Anomaly Detection: Transform data analysis and real-time anomaly detection using vectors to identify patterns and outliers.
• AI Agents: Unlock the potential of AI agents with powerful vector search and scalable infrastructure.

Customer Stories

• Hooman Sedghamiz, Director AI/ML, Bayer: "VectorStores are here to stay, making objects from image, sound, video, and text easily universal and searchable. I personally recommend Qdrant."
• Alex Webb, Director of Engineering, CB Insights: "Qdrant came out on top in ease of use, performance, pricing, and communication."
• Jeremy T. & Daly Singh, Generative AI Expert & Product Owner, Bosch: "With Qdrant, we found the missing piece to develop our own provider-independent multimodal generative AI platform on enterprise scale."

Integrations

Qdrant integrates seamlessly with all leading embeddings and frameworks, making it a versatile choice for various AI applications.

Getting Started

Deploy Qdrant locally with Docker using the Quick Start Guide or explore the main GitHub repository.

1. docker pull qdrant/qdrant
2. docker run -p 6333:6333 qdrant/qdrant

Qdrant is revolutionizing the way AI applications are built, offering high-performance vector search at scale, and enabling the next generation of AI solutions.