Learn how Aptabase and OpenReplay differ in their key features, development activity, technology stack and community adoption, so you can decide which of these product analytics is best for you.
Last 30 days
Last commit
Repository age
License
Repository

Last 30 days
Last commit
Repository age
Version
License
Self-hosted
Repository

OpenReplay appears to have several advantages over Aptabase, particularly in popularity, growth, maturity and features. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
OpenReplay significantly outpaces Aptabase in community adoption with 12,559 stars compared to 1,780 stars on GitHub. This 7.1x difference suggests OpenReplay has a much larger and more active community. In terms of developer contributions, OpenReplay has 807 forks, indicating moderate developer engagement.
OpenReplay is growing faster, adding 270 stars in the last 30 days (+2.2%) against adding 20 stars for Aptabase (+1.1%). OpenReplay is both larger and pulling further ahead.
Both projects show recent activity, with Aptabase last updated 11 days ago and OpenReplay 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: Aptabase uses C# while OpenReplay leverages Python, Golang, C, Objective-C, Swift, Ruby, Kotlin, MATLAB.
OpenReplay has been in development longer, starting 5 years ago, compared to Aptabase which began 3 years ago. This 1.9-year head start suggests OpenReplay may have more mature features and established processes.
Both projects use the AGPL-3.0 license, providing identical terms for usage and distribution.
Both tools serve similar use cases in Product Analytics. However, they also have distinct specializations: OpenReplay extends into Performance Monitoring (APM).
OpenReplay provides self-hosting options for complete data control and customization, while Aptabase may be primarily cloud-based or require different deployment approaches.