Milvus: High-Performance Vector Database
Milvus is an open-source vector database designed for similarity search and analytics on large-scale vector datasets. It's built to handle the demands of modern AI applications, offering scalability and speed.
Key Features:
- High Performance: Optimized for fast vector similarity searches.
- Scalability: Scale to tens of billions of vectors with minimal performance loss.
- GenAI Applications: Specifically designed for generative AI workloads.
- Flexible Deployment: Offers various deployment options, including Milvus Lite, Standalone, Distributed, and Zilliz Cloud.
- Integration with AI Tools: Plays well with LangChain, LlamaIndex, OpenAI, Hugging Face, and more.
- Feature-Rich: Supports metadata filtering, hybrid search, and multi-vector search.
Use Cases:
- RAG (Retrieval-Augmented Generation): Build RAG applications for enhanced content generation.
- Image Search: Implement image similarity search for managing and exploring image collections.
- Multimodal Search: Enable search across different data modalities.
- Hybrid Search: Combine vector similarity search with traditional filtering techniques.
Deployment Options:
- Milvus Lite: Lightweight, easy to start, ideal for learning and prototyping.
- Milvus Standalone: Robust, single-machine deployment for production or testing with datasets up to millions of vectors.
- Milvus Distributed: Scalable, enterprise-grade solution for handling billions of vectors.
- Zilliz Cloud: Fully managed Milvus service for hassle-free deployment and 10x faster performance.
