Milvus is an open source similarity search engine for massive-scale feature vectors. Built with heterogeneous computing architecture for the best cost efficiency. Searches over billion-scale vectors take only milliseconds with minimum computing resources. Milvus can be used in a wide variety of scenarios to boost AI development.
Heterogeneous computing
Milvus is designed with heterogeneous computing architecture for the best performance and cost efficiency.
Multiple indexes
Milvus supports a variety of indexing types that employs quantization, tree-based, and graph indexing techniques.
Intelligent resource management
Milvus automatically adapts search computation and index building processes based on your datasets and available resources.
Horizontal scalability
Milvus supports online / offline expansion to scale both storage and computation resources with simple commands.
High availability
Milvus is integrated with Kubernetes framework so that all single point of failures could be avoided.
Ease of use
Milvus can be easily installed in a few steps and supports Prometheus-based GUI monitor dashboards.
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