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Data as of May 29, 2026
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Great Expectations
Data quality framework for validating and profiling data pipelines
AI InfrastructureFounded 2018#17 of 55 in AI Infrastructure
Updated May 29, 2026
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Company profile
What is Great Expectations?
Great Expectations provides an open-source framework for data quality, enabling data teams to validate, profile, and document their data. It helps ensure the reliability and trustworthiness of data pipelines by defining 'expectations' about data, preventing issues before they impact downstream analytics or AI models. This makes it a critical tool for maintaining data integrity in modern data stacks.
Latest company data
Primary data point
Downloads
28.3M/30d
Tracked package: PyPI great-expectations
▼ -7%Updated 1d ago
Other data points
Dependent projects
117
Projects depending on tracked package: PyPI great-expectations
Updated 9h ago
GitHub stars
11.5K
Main repository stars
Updated 9h ago
Hacker News
1/30d
Position #49 in category discussion
Updated 9h ago
Repository health
Maintenance data from the main open-source repository.
OpenSSF ScorecardSource: OpenSSF ScorecardUpdates: WeeklyCaveat: Score 0–10 across security practices; not all checks apply to every repoMethodology →
4.2
Key-person riskSource: GitHub public event dataUpdates: WeeklyCaveat: Minimum developers needed for half of recent code changes. Lower = higher concentration risk.Methodology →
2
External contributorsSource: GitHub public event dataUpdates: WeeklyCaveat: Based on push events; may undercount contributors who only open PRsMethodology →
20
% of recent contributors outside the core team
Releases (30d)Source: GitHub release dataUpdates: WeeklyCaveat: Published releases in the last 30 daysMethodology →
0
Repository usage
Public repositories and source files importing packages tied to Great Expectations.
Repos importingMetric: Public GitHub repos using company packagesSource: ecosyste.ms Packages APIScope: UTC daily snapshotUpdates: DailyFreshness: 48h target; 48h expected source lagConfidence: HighCaveat: Public GitHub dependency data only; private repos and direct API use outside those packages are not visible.Methodology →
2840%
About Great Expectations
Great Expectations provides an open-source framework for data quality, enabling data teams to validate, profile, and document their data. It helps ensure the reliability and trustworthiness of data pipelines by defining 'expectations' about data, preventing issues before they impact downstream analytics or AI models. This makes it a critical tool for maintaining data integrity in modern data stacks.
FoundersAbe Gong, James Campbell, Kyle Eaton
Funding
$61M · 2 roundsRaised $61M total. Category position #17 of 55 in AI Infrastructure.
Series A2022
$40MTiger Global
Seed2021
$21MIndex Ventures, CRV
Investors
CRVIndex VenturesTiger Global
Tracked packages (1)
1 PyPI
great-expectations
PyPIMain PyPI packagegreat-expectations
Data quality framework for validating and profiling data pipelines