Learn how Umami and Vemetric differ in their key features, development activity, technology stack and community adoption, so you can decide which of these web analytics is best for you.
Last 30 days
Last commit
1 day agoRepository age
6 yearsVersion
v3.5.0License
MITSelf-hosted
YesRepository
umami-software/umami
Last 30 days
Last commit
11 hours agoRepository age
1 yearLicense
AGPL-3.0Repository
vemetric/vemetric
Umami appears to have several advantages over Vemetric, particularly in popularity, growth, maturity, licensing and features. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Umami significantly outpaces Vemetric in community adoption with 40,120 stars compared to 397 stars on GitHub. This 101.1x difference suggests Umami has a much larger and more active community. In terms of developer contributions, Umami has 8,542 forks, indicating strong developer engagement.
Umami is growing faster, adding 744 stars in the last 30 days (+1.9%) against adding 4 stars for Vemetric (+1%). Umami is both larger and pulling further ahead.
Both projects show recent activity, with Umami last updated 1 day ago and Vemetric 11 hours ago.
Both tools share common technology foundations, being built with JavaScript, Typescript, JSX. However, they differ in their additional technology choices: Umami uses CSS, Next.js.
Umami has been in development longer, starting 6 years ago, compared to Vemetric which began 1 year ago. This 5.0-year head start suggests Umami may have more mature features and established processes.
Umami uses the MIT license, which is more permissive than Vemetric's AGPL-3.0 license, potentially offering greater flexibility for commercial use and integration.
Both tools serve similar use cases in Web Analytics. However, they also have distinct specializations: Vemetric extends into Product Analytics.
Umami provides self-hosting options for complete data control and customization, while Vemetric may be primarily cloud-based or require different deployment approaches.
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs