Learn how Kanba and Planka differ in their key features, development activity, technology stack and community adoption, so you can decide which of these project management suites is best for you.
Last 30 days
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Repository age
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Last 30 days
Last commit
Repository age
Version
Self-hosted
Repository

Planka appears to have several advantages over Kanba, particularly in popularity, activity, maturity and features. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Planka significantly outpaces Kanba in community adoption with 12,584 stars compared to 657 stars on GitHub. This 19.2x difference suggests Planka has a much larger and more active community. In terms of developer contributions, Planka has 1,379 forks, indicating strong developer engagement.
Kanba and Planka are moving at much the same rate, adding 7 stars and adding 130 stars respectively over the last 30 days (+1.1% vs +1%). Neither is pulling away from the other on momentum alone.
Planka shows more recent development activity with its last commit 9 days ago, while Kanba was last updated 2 months ago. This suggests Planka is being more actively maintained.
Both tools share common technology foundations, being built with JavaScript, CSS, JSX. However, they differ in their additional technology choices: Kanba uses Typescript, Next.js while Planka leverages Bash, Python, SCSS.
Planka has been in development longer, starting 7 years ago, compared to Kanba which began 1 year ago. This 5.9-year head start suggests Planka may have more mature features and established processes.
Kanba is licensed under MIT, while Planka's license terms are not publicly specified.
Both tools serve similar use cases in Project Management Suites. However, they also have distinct specializations: Planka extends into Task Management, Agile Project Management.
Planka provides self-hosting options for complete data control and customization, while Kanba may be primarily cloud-based or require different deployment approaches.
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