Learn how DataLens and Lightdash differ in their key features, development activity, technology stack and community adoption, so you can decide which of these data visualization tools is best for you.
Last 30 days
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Self-hosted
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Last 30 days
Last commit
Repository age
Version
License
Self-hosted
Repository

Lightdash appears to have several advantages over DataLens, particularly in popularity, growth, maturity and licensing. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Lightdash significantly outpaces DataLens in community adoption with 6,075 stars compared to 1,698 stars on GitHub. This 3.6x difference suggests Lightdash has a much larger and more active community. In terms of developer contributions, Lightdash has 769 forks, indicating moderate developer engagement.
Lightdash is growing faster, adding 95 stars in the last 30 days (+1.6%) against adding 4 stars for DataLens (+0.2%). Lightdash is both larger and pulling further ahead.
Both projects show recent activity, with DataLens last updated 10 hours ago and Lightdash 8 hours ago.
Both tools share common technology foundations, being built with JavaScript, Bash. However, they differ in their additional technology choices: DataLens uses Python while Lightdash leverages CSS, Typescript, JSX, Next.js.
Lightdash has been in development longer, starting 5 years ago, compared to DataLens which began 3 years ago. This 2.5-year head start suggests Lightdash may have more mature features and established processes.
Lightdash uses the MIT license, which is more permissive than DataLens's Apache-2.0 license, potentially offering greater flexibility for commercial use and integration.
Both tools serve similar use cases in Data Visualization, BI Platforms. However, they also have distinct specializations: Lightdash extends into Semantic Layer Platforms.
Both DataLens and Lightdash offer self-hosting capabilities, giving you full control over your data and infrastructure.
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