A purpose-built tool for planning and building products
Linear vs Mollie
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
Linear (A purpose-built tool for planning and building products) and Mollie (Building a payments and banking stack for makers.) both appear on the Smoower Developer Ecosystem Index.
Linear (rank #103) holds a narrow lead over Mollie (rank #122) on the overall Smoower ecosystem score (55 vs 54). The gap of 1 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), Mollie is clearly ahead of Linear. On education (docs, guides and learning material for developers), Mollie is clearly ahead of Linear. On community (issue response, PR reviews and discussion health), Mollie is slightly ahead of Linear. On reach (how visible the ecosystem is beyond its own repos), Linear is clearly ahead of Mollie. On momentum (release cadence and how fast the ecosystem moves), Linear is slightly ahead of Mollie.
Linear carries 1,971 GitHub stars across 22 public repos, with 5 repositories active in the last 90 days and 21 external contributors on record. Mollie shows 2,571 stars across 85 public repos, 30 active in the last 90 days and 26 external contributors.
Linear is the stronger read for anyone weighting reach. Mollie looks better where education 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 | Linear | Mollie |
|---|---|---|
| Ranking | ||
| Overall rank | #103 | #122 |
| Pillars | ||
| Overall | 55 | 54 |
| Code | 45 | 69 |
| Education | 56 | 85 |
| Community | 36 | 41 |
| Reach | 76 | 21 |
| Momentum | 41 | 39 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 1,971 | 2,571 |
| Forks | 436 | 1,124 |
| Public repos | 22 | 85 |
| Active repos (90d) | 5 | 30 |
| External contributors | 21 | 26 |
| Avg polish | 42 | 63 |
| Avg AI-readiness | 31 | 50 |