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
Auto-fetched .

Stars
Forks
Last commit
Repository age
License
Self-hosted
Auto-fetched .

Apache Superset appears to have several advantages over DataLens, particularly in popularity 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 72,627 stars compared to 1,674 stars on GitHub. This 43.4x difference suggests Apache Superset has a much larger and more active community. In terms of developer contributions, Apache Superset has 17,149 forks, indicating strong developer engagement.
Both projects show recent activity, with Apache Superset last updated 12 hours ago and DataLens 22 days ago.
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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