Milvus
Milvus is an open-source vector database designed for GenAI applications, enabling high-speed searches and scaling to tens of billions of vectors with minimal performance loss.
Milvus is an open-source alternative to:
Milvus is an open-source vector database built for GenAI applications, enabling developers to perform high-speed searches and scale to tens of billions of vectors with minimal performance loss.
Key Features
- High-Performance Vector Search: Optimized for fast and accurate similarity searches across large datasets.
- Scalability: Supports standalone, distributed, and cloud-native deployments to handle millions or billions of vectors.
- Multi-Model Support: Enables hybrid, multimodal, and graph-based retrieval for advanced AI applications.
- Easy Integration: Compatible with popular AI frameworks like LangChain, LlamaIndex, OpenAI, and Hugging Face.
- Multiple Deployment Options:
- Milvus Lite: Lightweight, pip-installable version for prototyping.
- Milvus Standalone: Robust single-machine deployment for production.
- Milvus Distributed: Enterprise-grade, horizontally scalable solution.
- Zilliz Cloud: Fully managed Milvus with serverless and dedicated cluster options.
- Rich Tooling Ecosystem: Includes Attu (GUI), Milvus CLI, Backup, and Sizing Tool for operational efficiency.
- Open-Source Core: Community-driven development with enterprise-grade reliability.
Tech / Self-Hosting
Milvus is open-source and can be self-hosted in multiple configurations:
- Milvus Lite: Ideal for local development and testing.
- Milvus Standalone: Suitable for small to medium-scale production workloads.
- Milvus Distributed: Designed for large-scale, distributed deployments with high availability.
For managed solutions, Zilliz Cloud offers a fully managed Milvus experience with serverless and dedicated cluster options, including BYOC for compliance and security requirements.
Milvus is compatible with cloud storage solutions like S3 and supports integration with popular AI tools and frameworks, making it a versatile choice for GenAI applications.