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Koru vs SiYuan

Learn how Koru and SiYuan differ in their key features, development activity, technology stack and community adoption, so you can decide which of these note-taking tools is best for you.

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Koru

Write, organize, and run AI agents in a private workspace that stores everything locally, syncs peer-to-peer, and works offline on Windows, macOS, and Linux.
Screenshot of Koru

SiYuan

Personal knowledge management system with WYSIWYG block editing, bidirectional links, spaced repetition flashcards, a relational database, and end-to-end encrypted sync.
47,030stars+420(+0.9%)

Last 30 days

Screenshot of SiYuan

Detailed Comparison

SiYuan appears to have several advantages over Koru, particularly in popularity, maturity and features. Consider your specific needs regarding popularity, activity, maturity, licensing and features when making your decision.

SiYuan wins
Community & Popularity

SiYuan significantly outpaces Koru in community adoption with 47,030 stars compared to 29 stars on GitHub. This 1621.7x difference suggests SiYuan has a much larger and more active community. In terms of developer contributions, SiYuan has 3,093 forks, indicating strong developer engagement.

Comparable
Development Activity

Both projects show recent activity, with Koru last updated 4 hours ago and SiYuan 5 hours ago.

SiYuan wins
Project Maturity

SiYuan has been in development longer, starting 6 years ago, compared to Koru which began 25 days ago. This 6.2-year head start suggests SiYuan may have more mature features and established processes.

Comparable
Licensing

The projects use different licenses: Koru is licensed under MPL-2.0 while SiYuan uses AGPL-3.0. Consider the licensing requirements when choosing for your project.

Comparable
Use Cases & Features

Both tools serve similar use cases in Note-Taking, Personal Knowledge Management (PKM).

SiYuan wins
Hosting & Deployment

SiYuan provides self-hosting options for complete data control and customization, while Koru may be primarily cloud-based or require different deployment approaches.