Learn how Apache Superset and DataLens differ in their key features, development activity, technology stack and community adoption, so you can decide which of these bi platforms is best for you.
Stars
Forks
Last commit
Repository age
License
Self-hosted
Activity score

Stars
Forks
Last commit
Repository age
License
Self-hosted
Activity score

Apache Superset appears to have several advantages over DataLens, particularly in popularity, activity and maturity. Consider your specific needs regarding popularity, activity, technology, maturity, licensing and features when making your decision.
Apache Superset significantly outpaces DataLens in community adoption with 73,905 stars compared to 1,690 stars on GitHub. This 43.7x difference suggests Apache Superset has a much larger and more active community. In terms of developer contributions, Apache Superset has 17,918 forks, indicating strong developer engagement.
Apache Superset shows more recent development activity with its last commit 9 hours ago, while DataLens was last updated 1 month ago. This suggests Apache Superset is being more actively maintained.
Both tools share common technology foundations, being built with JavaScript, Bash, Python. However, they differ in their additional technology choices: Apache Superset uses CSS, Typescript, JSX.
Apache Superset has been in development longer, starting 11 years ago, compared to DataLens which began 3 years ago. This 8.3-year head start suggests Apache Superset may have more mature features and established processes.
Both projects use the Apache-2.0 license, providing identical terms for usage and distribution.
Both tools serve similar use cases in BI Platforms, Data Visualization.
Both Apache Superset and DataLens offer self-hosting capabilities, giving you full control over your data and infrastructure.
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