36 lines
1.3 KiB
Markdown
36 lines
1.3 KiB
Markdown
---
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title: "Qdrant"
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type: entity
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tags: [vector-database, rag, rust, open-source]
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sources: ["RAG从入门到精通系列1：基础RAG"]
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last_updated: 2026-04-16
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---
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## Basic Information
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- **Type**: Vector Database
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- **Source**: RAG从入门到精通系列1：基础RAG
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## Definition
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Qdrant is an open-source vector database written in Rust, designed for storing and searching high-dimensional embedding vectors with high performance.
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## Key Features
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- **Written in Rust**: High performance and memory safety
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- **Vector Search**: Supports similarity search with various metrics
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- **Open Source**: Freely available for self-hosting
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- **RAG Integration**: Commonly used as the vector store in RAG pipelines
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## Technical Details
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- Implements various similarity comparison methods for embedding vectors
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- Supports Top-k retrieval (returning k most similar results)
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- Can store metadata alongside vectors
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## Related Concepts
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- [[向量数据库]]：Qdrant is a specific vector database implementation
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- [[Embedding]]：Qdrant stores embedding vectors
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- [[RAG]]：Qdrant serves as the storage layer in RAG systems
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- [[LangChain]]：LangChain can integrate with Qdrant as a vector store
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## Related Entities
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- [[BAAI]]：Embedding models that feed data into Qdrant
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- [[Qwen]]：LLM that queries Qdrant via retrieval
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