Learn how Icinga and ProjectDiscovery differ in their key features, development activity, technology stack and community adoption, so you can decide which of these infrastructure monitoring tools is best for you.
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Last 30 days
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Version
License
Repository

Both Icinga and ProjectDiscovery 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.
ProjectDiscovery significantly outpaces Icinga in community adoption with 30,602 stars compared to 2,232 stars on GitHub. This 13.7x difference suggests ProjectDiscovery has a much larger and more active community. In terms of developer contributions, ProjectDiscovery has 3,805 forks, indicating strong developer engagement.
ProjectDiscovery is growing faster, adding 739 stars in the last 30 days (+2.5%) against adding 14 stars for Icinga (+0.6%). ProjectDiscovery is both larger and pulling further ahead.
Both projects show recent activity, with Icinga last updated 19 hours ago and ProjectDiscovery 3 days ago.
Both tools share common technology foundations, being built with JavaScript, Bash, Python. However, they differ in their additional technology choices: Icinga uses C, Objective-C, C++, C# while ProjectDiscovery leverages Typescript, Golang, Java.
Icinga has been in development longer, starting 13 years ago, compared to ProjectDiscovery which began 6 years ago. This 6.7-year head start suggests Icinga may have more mature features and established processes.
ProjectDiscovery uses the MIT license, which is more permissive than Icinga's GPL-3.0 license, potentially offering greater flexibility for commercial use and integration.
Both tools serve similar use cases in Infrastructure Monitoring. However, they also have distinct specializations: ProjectDiscovery extends into Security Automation (SIEM/SOAR), Vulnerability Scanning.
Icinga provides self-hosting options for complete data control and customization, while ProjectDiscovery may be primarily cloud-based or require different deployment approaches.