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Milvus is an open-source vector database designed for efficient similarity search and retrieval of high-dimensional embeddings. It provides scalable indexing, hybrid search and distributed deployment features for production ML and search systems. Typical uses include semantic search, recommendations and anomaly detection based on embeddings.
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Milvus is Zilliz's open-source vector database for similarity search and storing high-dimensional vectors in AI applications.
Zilliz developed Milvus from the need to provide scalable vector search over large collections of unstructured data. The project was released as open source in 2019 and moved to the Linux Foundation in 2021.
An embedding is stored as a point in a high-dimensional space. Milvus builds a search index, finds nearby points, and joins them to their associated documents or metadata.
A numeric representation that captures semantic similarity.
Speeds up searches for similar vectors.
Restricts a search with structured criteria.
Milvus supports scalable semantic search and RAG; embeddings, index parameters, and update strategies determine quality and cost.
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