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Milvus vs Qdrant

Learn how Milvus and Qdrant differ in their key features, development activity, technology stack and community adoption, so you can decide which of these vector databases is best for you.

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Favicon of Milvus

Milvus

AI
Open-source vector database optimized for similarity search, scaling to billions of vectors with minimal performance loss
45,698stars+415(+0.9%)

Last 30 days

Screenshot of Milvus
Favicon of Qdrant

Qdrant

AI
Qdrant is an open-source vector database that provides high-performance similarity search for AI and machine learning applications.
34,062stars+629(+1.9%)

Last 30 days

Screenshot of Qdrant

Detailed Comparison

Both Milvus and Qdrant have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.

Comparable
Community & Popularity

Both tools have similar popularity levels, with Milvus having 45,698 stars and Qdrant having 34,062 stars on GitHub. In terms of developer contributions, Milvus has 4,185 forks, indicating strong developer engagement.

Qdrant wins
Growth Momentum

Qdrant is growing faster, adding 629 stars in the last 30 days (+1.9%) against adding 415 stars for Milvus (+0.9%). Qdrant is the smaller project of the two, so it is closing the gap rather than extending a lead.

Comparable
Development Activity

Both projects show recent activity, with Milvus last updated 10 hours ago and Qdrant 10 hours ago.

Comparable
Technology Stack

Both tools share common technology foundations, being built with JavaScript, Bash, Python, C, Rust, Objective-C. However, they differ in their additional technology choices: Milvus uses CSS, Golang, C++.

Comparable
Project Maturity

Both projects started around the same time, with Milvus beginning 7 years ago and Qdrant 6 years ago.

Comparable
Licensing

Both projects use the Apache-2.0 license, providing identical terms for usage and distribution.

Comparable
Use Cases & Features

Both tools serve similar use cases in Vector Databases.