Avalara vs Loop Returns
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
Avalara and Loop Returns (Loop public repository) both appear on the Smoower Developer Ecosystem Index.
Loop Returns (rank #625) holds a narrow lead over Avalara (rank #696) on the overall Smoower ecosystem score (33 vs 31). The gap of 2 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), Avalara is slightly ahead of Loop Returns. On education (docs, guides and learning material for developers), Loop Returns is clearly ahead of Avalara. On community (issue response, PR reviews and discussion health), Avalara is ahead of Loop Returns. On reach (how visible the ecosystem is beyond its own repos), Avalara is slightly ahead of Loop Returns.
Avalara carries 21 GitHub stars across 7 public repos, with 0 repositories active in the last 90 days and 0 external contributors on record. Loop Returns shows 1 stars across 2 public repos, 0 active in the last 90 days and 0 external contributors. The star gap on its own does not decide the comparison, but Avalara's footprint is roughly 21.0x larger, which usually shows up in downstream signals like inbound issues and third party integrations.
Avalara is the stronger read for anyone weighting community. Loop Returns 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 | Avalara | Loop Returns |
|---|---|---|
| Ranking | ||
| Overall rank | #696 | #625 |
| Pillars | ||
| Overall | 31 | 33 |
| Code | 38 | 32 |
| Education | 57 | 80 |
| Community | 18 | 4 |
| Reach | 24 | 21 |
| Momentum | 0 | 0 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 21 | 1 |
| Forks | 29 | 1 |
| Public repos | 7 | 2 |
| Active repos (90d) | 0 | 0 |
| External contributors | 0 | 0 |
| Avg polish | 44 | 28 |
| Avg AI-readiness | 19 | 38 |