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Intro

Milvus is an open-source vector database designed to store, index, and search high-dimensional data (like embeddings from AI models). It helps you quickly find items that are “similar” — based on meaning, image features, sound, etc.

Pros​

  • Very fast and scalable
  • Flexible indexing and hybrid search
  • Strong open-source support and large community
  • Optimized for AI/ML pipelines

Cons​

  • No built-in knowledge graph features (unlike Weaviate)
  • Needs external tools for document chunking, embedding, and RAG orchestration
  • Graph integration (e.g., with Graphiti) may need custom development

Weaviate vs Milvus​

  • Weaviate: Offers a more holistic solution with its combined vector and graph capabilities, making it well-suited for applications requiring semantic understanding and complex relationship modeling.
  • Milvus: Excels in high-performance vector search for large-scale datasets but may require additional tools for advanced graph functionalities.

If primary focus is on semantic search and leveraging knowledge graphs, Weaviate would be the preferred choice.However, if application demands high-throughput vector searches over massive datasets, Milvus would be more appropriate.