Subscription Analytics Platform
ChartMogul vs UptimeRobot
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
ChartMogul (Subscription Analytics Platform) and UptimeRobot (Leading Uptime Monitoring Service) both appear on the Smoower Developer Ecosystem Index.
ChartMogul (rank #401) holds a narrow lead over UptimeRobot (rank #510) on the overall Smoower ecosystem score (41 vs 37). The gap of 4 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), ChartMogul is ahead of UptimeRobot. On education (docs, guides and learning material for developers), UptimeRobot is slightly ahead of ChartMogul. On community (issue response, PR reviews and discussion health), ChartMogul is ahead of UptimeRobot. On reach (how visible the ecosystem is beyond its own repos), UptimeRobot is ahead of ChartMogul. On momentum (release cadence and how fast the ecosystem moves), UptimeRobot is clearly ahead of ChartMogul.
ChartMogul carries 112 GitHub stars across 21 public repos, with 7 repositories active in the last 90 days and 3 external contributors on record. UptimeRobot shows 81 stars across 9 public repos, 6 active in the last 90 days and 10 external contributors.
ChartMogul is the stronger read for anyone weighting community. UptimeRobot looks better where momentum is the deciding factor. The table below breaks the scores down pillar by pillar; the linked profiles cover the underlying repos, docs and community signals in full.
Side-by-side metrics
| Metric | ChartMogul | UptimeRobot |
|---|---|---|
| Ranking | ||
| Overall rank | #401 | #510 |
| Pillars | ||
| Overall | 41 | 37 |
| Code | 47 | 38 |
| Education | 54 | 62 |
| Community | 53 | 35 |
| Reach | 14 | 28 |
| Momentum | 30 | 52 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 112 | 81 |
| Forks | 64 | 24 |
| Public repos | 21 | 9 |
| Active repos (90d) | 7 | 6 |
| External contributors | 3 | 10 |
| Avg polish | 41 | 39 |
| Avg AI-readiness | 43 | 37 |