GitDealFlowsignals

Q3 2025 · United States

Data Infrastructure Startups in United States to Watch, Q3 2025

6 data infrastructure startups based in United States ranked by GitHub engineering acceleration. Filtered from our broader Data Infrastructure sector rankings.

#CompanyStageCommits (14d)ChangeContributorsSignal
1PostHog

The single platform to analyze, test, observe, and deploy new features

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Growth1,243+10%391Framework migration
2dagster-io

An orchestration platform for the development, production, and observation of data assets.

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Growth182+2%407Framework migration
3ClickHouse

The leading database for AI

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Growth1,669+1%309Framework migration
4redpanda-data

The streaming data platform for developers

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Growth355-20%175Deceleration
5airbytehq

Open source data replication platform and context layer for AI agents.

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Growth579-23%378Deceleration
6VictoriaMetrics

Easy to use and fast monitoring solution

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Growth52-28%392Deceleration
Powered by VC Deal Flow Signal , real-time GitHub engineering data for investorsData from public GitHub API

Sorted by commit velocity change (14-day window, descending). Data last updated Q3 2025. Geography from GitHub org profiles.

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Frequently Asked Questions

Which data infrastructure startups in United States are showing the strongest engineering signals in Q3 2025?

In Q3 2025, PostHog leads data infrastructure startups in United States with 1243 commits over a 14-day window (+10% change) and 391 active contributors. Across all 6 tracked United States-based startups in this sector, the average 14-day commit velocity is 680 commits. The dominant signal pattern is "Framework migration", which typically indicates significant technical migration, which often precedes a pivot or platform upgrade.

How does the United States data infrastructure startup ecosystem compare to other regions?

United States accounts for 6 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.

How is startup geography determined in these rankings?

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.

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