Learn how Bklit and Databuddy 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.
Stars
Forks
Last commit
Repository age
Self-hosted
Auto-fetched .

Stars
Forks
Last commit
Repository age
License
Auto-fetched .

Both Bklit and Databuddy have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, activity, technology, maturity, licensing and features when making your decision.
Databuddy significantly outpaces Bklit in community adoption with 995 stars compared to 248 stars on GitHub. This 4.0x difference suggests Databuddy has a much larger and more active community. In terms of developer contributions, Databuddy has 179 forks, indicating moderate developer engagement.
Both projects show recent activity, with Bklit last updated 22 days ago and Databuddy 10 hours ago.
Both tools share common technology foundations, being built with JavaScript, CSS, Bash, Typescript, JSX, Next.js. However, they differ in their additional technology choices: Databuddy leverages Rust.
Both projects started around the same time, with Bklit beginning 11 months ago and Databuddy 1 year ago.
Databuddy is licensed under AGPL-3.0, while Bklit's license terms are not publicly specified.
Both tools serve similar use cases in Web Analytics. However, they also have distinct specializations: Databuddy extends into Product Analytics.
Bklit provides self-hosting options for complete data control and customization, while Databuddy 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