Learn how Apache Superset and Redash 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
Last commit
3 hours agoRepository age
11 yearsVersion
6.1.0License
Apache-2.0Self-hosted
YesRepository
apache/superset
Last 30 days
Last commit
19 hours agoRepository age
13 yearsVersion
v26.9.0License
BSD-2-ClauseRepository
getredash/redash
Both Apache Superset and Redash have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Apache Superset leads in popularity with 75,370 stars vs 28,853 stars for Redash. The 161% higher star count indicates stronger community adoption. In terms of developer contributions, Apache Superset has 18,558 forks, indicating strong developer engagement.
Apache Superset is growing faster, adding 383 stars in the last 30 days (+0.5%) against adding 25 stars for Redash (+0.1%). Apache Superset is both larger and pulling further ahead.
Both projects show recent activity, with Apache Superset last updated 3 hours ago and Redash 19 hours ago.
Both tools share common technology foundations, being built with JavaScript, CSS, Typescript, JSX, Python. However, they differ in their additional technology choices: Apache Superset uses Bash.
Redash has been in development longer, starting 13 years ago, compared to Apache Superset which began 11 years ago. This 1.8-year head start suggests Redash may have more mature features and established processes.
Redash uses the BSD-2-Clause license, which is more permissive than Apache Superset'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.
Apache Superset provides self-hosting options for complete data control and customization, while Redash may be primarily cloud-based or require different deployment approaches.