We chose Milvus because it is very user-friendly. Without Milvus, our semantic search wouldn’t have been 10x smarter!
Milvus improves upon high-performance storage and index libraries such as Faiss and hnswlib, guaranteeing time and resource efficient query speeds. Using a variety of acceleration methods (e.g., CPU, SIMD, GPU, and FPGA), Milvus can retrieve vector data on trillion-scale datasets in milliseconds.
Milvus is cloud native and can be horizontally scaled with ease. The platform is capable of handling storage and computation at any scale, and has a microservice design that supports on-demand and automatic scaling.
Built for Unstructured Data
Milvus helps users focus on the semantic meaning of unstructured data rather than complexities such as sharding, data persistence, and load balancing. Milvus supports high-performance, hybrid search of vector and scalar data, opening up new possibilities for unstructured data processing.
Milvus is a graduate of the LF AI & Data Foundation's incubator program and has been adopted by 1,000+ organizations worldwide. The platform's vibrant open-source community welcomes contributions from everyone.
Milvus supports multiple data types and provides comprehensive multi-language SDKs. Through the Python-ORM API, Milvus offers an integrated user experience across laptops, local clusters, and the cloud. A wealth of deployment and visualization tools are available to help users get Milvus up and running faster.
Join the community
Milvus is open-sourced on GitHub.
Contributions and feedbacks are welcome!