wiki-ingest: RAG从入门到精通系列1

wiki/entities/Qdrant.md

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+---
+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