Next-gen newsletter platform on a mission to help creators and businesses seamlessly create, monetize, and grow their audiences.
beehiiv vs Marqeta
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
beehiiv (Next-gen newsletter platform on a mission to help creators and businesses seamlessly create, monetize, and grow their audiences.) and Marqeta both appear on the Smoower Developer Ecosystem Index.
beehiiv (rank #510) holds a narrow lead over Marqeta (rank #662) on the overall Smoower ecosystem score (37 vs 32). The gap of 5 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), beehiiv is slightly ahead of Marqeta. On education (docs, guides and learning material for developers), beehiiv is ahead of Marqeta. On community (issue response, PR reviews and discussion health), beehiiv is slightly ahead of Marqeta. On reach (how visible the ecosystem is beyond its own repos), beehiiv is slightly ahead of Marqeta.
beehiiv carries 33 GitHub stars across 13 public repos, with 4 repositories active in the last 90 days and 3 external contributors on record. Marqeta shows 84 stars across 18 public repos, 3 active in the last 90 days and 1 external contributors.
beehiiv is the stronger read for anyone weighting education. Marqeta makes more sense for teams already using its adjacent tools. 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 | beehiiv | Marqeta |
|---|---|---|
| Ranking | ||
| Overall rank | #510 | #662 |
| Pillars | ||
| Overall | 37 | 32 |
| Code | 40 | 39 |
| Education | 70 | 59 |
| Community | 14 | 12 |
| Reach | 46 | 40 |
| Momentum | 15 | 15 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 33 | 84 |
| Forks | 6 | 42 |
| Public repos | 13 | 18 |
| Active repos (90d) | 4 | 3 |
| External contributors | 3 | 1 |
| Avg polish | 40 | 43 |
| Avg AI-readiness | 30 | 22 |