---
title: "Qdrant"
type: entity
tags: [vector-database, rag, rust, open-source]
sources: ["RAG从入门到精通系列1：基础RAG"]
last_updated: 2026-04-16
---

## Basic Information
- **Type**: Vector Database
- **Source**: RAG从入门到精通系列1：基础RAG

## Definition
Qdrant is an open-source vector database written in Rust, designed for storing and searching high-dimensional embedding vectors with high performance.

## Key Features
- **Written in Rust**: High performance and memory safety
- **Vector Search**: Supports similarity search with various metrics
- **Open Source**: Freely available for self-hosting
- **RAG Integration**: Commonly used as the vector store in RAG pipelines

## Technical Details
- Implements various similarity comparison methods for embedding vectors
- Supports Top-k retrieval (returning k most similar results)
- Can store metadata alongside vectors

## Related Concepts
- [[向量数据库]]：Qdrant is a specific vector database implementation
- [[Embedding]]：Qdrant stores embedding vectors
- [[RAG]]：Qdrant serves as the storage layer in RAG systems
- [[LangChain]]：LangChain can integrate with Qdrant as a vector store

## Related Entities
- [[BAAI]]：Embedding models that feed data into Qdrant
- [[Qwen]]：LLM that queries Qdrant via retrieval