We chose Milvus because it is very user-friendly. Without Milvus, our semantic search wouldn’t have been 10x smarter!
Milvus drastically accelerated retrieval of millions of semantic vectors. We saw a near tenfold advancement compared to how things were when we were using other vector similarity search engines.
We are looking forward to any future updates from Milvus that could help us further optimize the shopping experience for our users.
The fast similarity search provided by Milvus allows ArtLens AI to match user uploaded photos with visually similar art from the CMA’s massive collection in seconds.
Without a vector search engine like Milvus, similarity searches would not be feasible across the entire vector space.
The Milvus community is very active and has an abundance of resources available for its users. This helped us quickly developed a minimum viable product (MVP) and significantly lowered the development costs.
Without Milvus, building our news aggregator wouldn't have been possible. The platform maintains consistent performance levels even in situations with unusually high concurrency.
Milvus’ flexibility makes it easy to optimize machine learning projects to better fit different scenarios.
Features
Cost-efficient
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.
On-demand Performance
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.
Community-backed
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.
User-friendly
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.
Users
Join the community
Milvus is open-sourced on GitHub.
Contributions and feedbacks are welcome!
What is Milvus?
Open-source vector database for unstructured data.
Contribute
Milvus is a community project. We encourage you to join the effort and contribute feedback, ideas and code.
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Milvus, and associated open source project names are trademarks of the LF AI & Data Foundation.