Qdrant Documentation

Qdrant is an AI-native vector search and a semantic search engine. You can use it to extract meaningful information from unstructured data.

Clone this repo now and build a search engine in five minutes.

Cloud Quickstart Local Quickstart

Introducing Qdrant Edge

Qdrant Edge is a lightweight, embedded vector search engine for in-process retrieval — no background services, minimal memory footprint, and no network required. Built for robots, kiosks, mobile devices, and any environment requiring offline-capable AI search.

Run vector search anywhere, even offline

Qdrant User Manual

Learn how to manage your data, run powerful searches, and leverage inference to build AI-native applications.

Vectors

Manage Data

Create collections, manage vectors, payloads, and storage. Learn about indexing, quantization, and multitenancy.

Search

Learn about similarity search, filtering, hybrid queries, and advanced retrieval techniques.

Inference

Inference

Configure dense, sparse, and multi-vector embeddings. Use cloud-hosted embedding models directly with Qdrant.

Support

Get help from the Qdrant community or contact our support team.

Community Support

Join 6,000+ active members to learn, collaborate, and participate in Qdrant's latest activities.

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Qdrant Cloud Support

Paying customers have access to our Support team. Links to the support portal are available in the Qdrant Cloud Console.