Get scalable vector ANN search with Milvus, a cloud-native database for founders, backed by 45k+ GitHub stars
44,588 stars4,035 forksGoQuality 9/10Updated 6/2/2026100% free ยท open source
What it does
Milvus is a cloud-native database that enables scalable vector Approximate Nearest Neighbors (ANN) search for founders to efficiently manage and query large datasets of vectors.
When to use it
โขBuilding a recommendation system that requires fast and accurate similarity searches
โขDeveloping a computer vision application that needs to efficiently query large datasets of image embeddings
โขCreating a natural language processing model that requires scalable semantic search capabilities
Quick start
1Create a new Milvus server instance by running the command: `docker run -d --name milvus-db -p 19530:19530 -v /tmp/milvus:/var/lib/milvus milvusdb/milvus:latest`
2Use the Milvus Python SDK to connect to the server: `from milvus import Milvus, Client`
3Create a new index and insert data into the Milvus database: `client.create_index('test', 'ivf_sq8')` and `vectors = [[1.0, 2.0], [3.0, 4.0]]`
4Perform a vector search query: `client.search('test', 'ivf_sq8', vectors)`