Product Insights
We do love open source and have an opportunity to make it better from now.
Heap vs Semrush
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
Heap (Product Insights) and Semrush (We do love open source and have an opportunity to make it better from now.) both appear on the Smoower Developer Ecosystem Index.
Semrush (rank #317) holds a modest lead over Heap (rank #569) on the overall Smoower ecosystem score (44 vs 35). The gap of 9 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), Semrush is ahead of Heap. On education (docs, guides and learning material for developers), Heap is slightly ahead of Semrush. On community (issue response, PR reviews and discussion health), Semrush is clearly ahead of Heap. On reach (how visible the ecosystem is beyond its own repos), Semrush is slightly ahead of Heap. On momentum (release cadence and how fast the ecosystem moves), Semrush is clearly ahead of Heap.
Heap carries 215 GitHub stars across 65 public repos, with 6 repositories active in the last 90 days and 1 external contributors on record. Semrush shows 454 stars across 11 public repos, 2 active in the last 90 days and 7 external contributors.
Heap is the stronger read for anyone weighting education. Semrush 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 | Heap | Semrush |
|---|---|---|
| Ranking | ||
| Overall rank | #569 | #317 |
| Pillars | ||
| Overall | 35 | 44 |
| Code | 35 | 44 |
| Education | 72 | 65 |
| Community | 14 | 36 |
| Reach | 30 | 35 |
| Momentum | 12 | 37 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 215 | 454 |
| Forks | 105 | 124 |
| Public repos | 65 | 11 |
| Active repos (90d) | 6 | 2 |
| External contributors | 1 | 7 |
| Avg polish | 37 | 48 |
| Avg AI-readiness | 23 | 32 |