Learn how DataLens and Grafana 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.
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Grafana 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.
Grafana significantly outpaces DataLens in community adoption with 74,321 stars compared to 1,684 stars on GitHub. This 44.1x difference suggests Grafana has a much larger and more active community. In terms of developer contributions, Grafana has 14,041 forks, indicating strong developer engagement.
Both projects show recent activity, with DataLens last updated 5 days ago and Grafana 1 hour ago.
Both tools share common technology foundations, being built with JavaScript, Bash, Python. However, they differ in their additional technology choices: Grafana leverages CSS, Typescript, JSX, Golang, Ruby.
Grafana has been in development longer, starting 13 years ago, compared to DataLens which began 3 years ago. This 9.9-year head start suggests Grafana may have more mature features and established processes.
The projects use different licenses: DataLens is licensed under Apache-2.0 while Grafana uses AGPL-3.0. Consider the licensing requirements when choosing for your project.
Both tools serve similar use cases in Data Visualization. However, they also have distinct specializations: DataLens also focuses on BI Platforms while Grafana extends into Infrastructure Monitoring, Performance Monitoring (APM).
Both DataLens and Grafana offer self-hosting capabilities, giving you full control over your data and infrastructure.