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Q3 2025 · United States
5 data infrastructure startups based in United States ranked by GitHub engineering acceleration. Filtered from our broader Data Infrastructure sector rankings.
| # | Company | Stage | Geo | Commits (14d) | Change | Contributors | Contrib. Growth | New Repos | Signal |
|---|---|---|---|---|---|---|---|---|---|
| 1 | PostHog The single platform to analyze, test, observe, and deploy new features View signal profile → | Growth | US | 184 | +24% | 100 | +0% | 3 | Infrastructure buildout |
| 2 | VictoriaMetrics Easy to use and fast monitoring solution View signal profile → | Growth | US | 96 | +10% | 100 | +0% | 0 | Framework migration |
| 3 | ClickHouseView signal profile → | Growth | US | 1,824 | -1% | 100 | +0% | 4 | Infrastructure buildout |
| 4 | airbytehq Simple & extensible open-source data integration View signal profile → | Growth | US | 721 | -10% | 100 | +0% | 0 | Framework migration |
| 5 | dagster-io An orchestration platform for the development, production, and observation of data assets. View signal profile → | Growth | US | 85 | -61% | 100 | +19% | 1 | Framework migration |
Sorted by commit velocity change (14-day window, descending). Data last updated Q3 2025. Geography from GitHub org profiles.
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In Q3 2025, PostHog leads data infrastructure startups in United States with 184 commits over a 14-day window (+24% change) and 100 active contributors. Across all 5 tracked United States-based startups in this sector, the average 14-day commit velocity is 582 commits. The dominant signal pattern is "Framework migration", which typically indicates significant technical migration, which often precedes a pivot or platform upgrade.
United States accounts for 5 of the data infrastructure startups in our tracking dataset for Q3 2025. This geographic view filters the broader sector rankings to help investors focused on United States-based deal flow identify engineering acceleration patterns within their target geography. Regional concentrations often reflect local regulatory environments, talent pools, and investor networks that shape startup trajectories differently from global averages.
We derive startup geography primarily from the GitHub organization profile location field, supplemented by a manually curated enrichment database of known startup headquarters. This means startups without a public GitHub location may appear in our global sector rankings but not in geographic filters. The geographic classification uses broad regions (United States, etc.) rather than city-level granularity to provide meaningful sample sizes for comparison.