Great Expectations
Observability
Overview
Great Expectations is an open-source data quality testing and validation framework that enables data teams to define, test, and document data quality expectations. It provides assertions for data quality, automated profiling, data documentation, and integration with popular data tools. Great Expectations supports pipeline testing, data contracts, and integrates with Airflow, Spark, and cloud data platforms.
- Pricing model
- Freemium
- Deployment
- Self-hosted / on-premises, SaaS (vendor-hosted)
- Regions served
- Global
- Categories
- Software & technology, Workflow orchestration, Observability, Self-hosted / on-premises, MLOps & model tooling, Predictive / classical ML, Freemium, SaaS (vendor-hosted)
- Last updated
- 2 October 2026
- Published
- 2 October 2026
Use cases
Deployment options
Data sources & provenance
Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.
- Data quality
- Data quality: Editorially Reviewed
- Primary source
- greatexpectations.io
- Sources cited
- 2
- Last reviewed
- 28 September 2026
- Last updated
- 2 October 2026
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