Learn how Canonry and OneGlanse differ in their key features, development activity, technology stack and community adoption, so you can decide which of these ai visibility tracking is best for you.
Last 30 days
Last commit
8 hours agoRepository age
8 monthsVersion
v7.50.0License
MITSelf-hosted
YesRepository
canonry/canonry
Last 30 days
Last commit
3 days agoRepository age
1 yearLicense
MITSelf-hosted
YesRepository
oneglanse/oneglanse
Both Canonry and OneGlanse 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.
Both tools have similar popularity levels, with Canonry having 209 stars and OneGlanse having 258 stars on GitHub. In terms of developer contributions, OneGlanse has 48 forks, indicating growing developer engagement.
OneGlanse is growing faster, adding 38 stars in the last 30 days (+17%) against adding 24 stars for Canonry (+13%). OneGlanse is both larger and pulling further ahead.
Both projects show recent activity, with Canonry last updated 8 hours ago and OneGlanse 3 days ago.
Both tools share common technology foundations, being built with JavaScript, CSS, Bash, Typescript, JSX. However, they differ in their additional technology choices: Canonry uses PHP while OneGlanse leverages Next.js.
Both projects started around the same time, with Canonry beginning 8 months ago and OneGlanse 1 year ago.
Both projects use the MIT license, providing identical terms for usage and distribution.
Both tools serve similar use cases in AI Visibility Tracking. However, they also have distinct specializations: Canonry also focuses on SEO Tools.
Both Canonry and OneGlanse offer self-hosting capabilities, giving you full control over your data and infrastructure.