The most popular vector database for enterprise users
Fuel your machine learning deployment
Store, index, and manage massive embedding vectors generated by deep neural networks and other machine learning (ML) models.
Easy to Use
With Milvus vector database, you can create a large scale similarity search service in less than a minute. Simple and intuitive SDKs are also available for a variety of different languages.
Milvus is hardware efficient and provides advanced indexing algorithms, achieving a 10x performance boost in retrieval speed.
Milvus vector database has been battle-tested by over a thousand enterprise users in a variety of use cases. With extensive isolation of individual system components, Milvus is highly resilient and reliable.
The distributed and high-throughput nature of Milvus makes it a natural fit for serving large scale vector data.
Milvus vector database adopts a systemic approach to cloud-nativity, separating compute from storage and allowing you to scale both up and out.
Support for various data types, enhanced vector search with attribute filtering, UDF support, configurable consistency level, time travel, and more.
# Download milvus-standalone-docker-compose.yml and save it as docker-compose.yml manually
wget https://github.com/milvus-io/milvus/releases/download/v2.3.3/milvus-standalone-docker-compose.yml -O docker-compose.yml
# In the same directory as the docker-compose.yml file, start up Milvus
sudo docker compose up -d
Simplified development with Attu
(Thanks for contribution from Zilliz)
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