Comparison
great_expectations vs piperider
Verdict
Pick great_expectations if great Expectations is a Python library that helps maintain data quality through unit testing mechanisms known as expectations; pick piperider if pipeRider is designed to automatically compare data and highlight differences between branches for dbt models before merging pull requests, ensuring data quality in the CI/CD pipeline of dbt projects.
Markdown twin · great_expectations alternatives · piperider alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | great_expectations | piperider |
|---|---|---|
| Maintenance | Very active (0d since push) As of 3w · github_public_v1 | Dormant (577d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No published findings from this source as of 2026-07-11 As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- great_expectations
- Always know what to expect from your data
- piperider
- Code review for data in dbt
Stars
- great_expectations
- 12k
- piperider
- 495
Forks
- great_expectations
- 1.8k
- piperider
- 23
Open issues
- great_expectations
- 39
- piperider
- 20
Language
- great_expectations
- Python
- piperider
- Python
Adopt for
- great_expectations
- Great Expectations is a Python library that helps maintain data quality through unit testing mechanisms known as expectations.
- piperider
- PipeRider is designed to automatically compare data and highlight differences between branches for dbt models before merging pull requests, ensuring data quality in the CI/CD pipeline of dbt projects.
Persona
- great_expectations
- -
- piperider
- -
Runtime
- great_expectations
- -
- piperider
- -
License
- great_expectations
- Great Expectations is available under the Apache-2.0 license.
- piperider
- Apache-2.0
Last pushed
- great_expectations
- Aug 2, 2026
- piperider
- Jan 3, 2025
Categories
- great_expectations
- Data & Retrieval
- piperider
- Data & Retrieval, Evaluation & Observability
Trust and health
Maintenance
- great_expectations
- Very active (96%)
- piperider
- Dormant (18%)
Days since push
- great_expectations
- 0d
- piperider
- 577d
Open issues (now)
- great_expectations
- 39
- piperider
- 20
OSV dependency advisories
- great_expectations
- Published findings
- piperider
- No published findings from this source as of 2026-07-11
Full report
- great_expectations
- Trust report
- piperider
- Trust report
Shared compatibility
- Python · great_expectations: Python runtime · piperider: Python runtime
Choose great_expectations if…
- Requirements: Supports Python versions 3.10 through 3.13, with experimental support for Python 3.14 and later via an environment variable..
- Tags unique to great_expectations: data-engineering, data-quality, mlops.
- When you need detailed and automated documentation for each set of validation results to simplify your data quality processes while preserving institutional knowledge.
When NOT to use great_expectations
- For environments that strictly require adherence to Python versions 3.9 or lower, since Great Expectations supports only 3.10 through 3.13 natively.
- If your data integration requirements are not compatible with those listed in the Great Expectations compatibility reference.
Choose piperider if…
- Requirements: Requires a pre-existing dbt project with defined connection profiles.; Must be installed through Python using the package manager pip and may need specific connectors based on data source..
- Tags unique to piperider: code-review, continuous-integration, data-observability, data-profiling.
- Also covers Evaluation & Observability.
- piperider ships Docker support for self-hosted deployment.
- When working with dbt models where pre-merge data validation is essential to detect changes that impact downstream models.
When NOT to use piperider
- Consider other tools if continuous support and active development are required, as PipeRider has been superseded by Recce and will no longer receive regular updates.
- Avoid using if your project requires real-time data testing or monitoring; PipeRider is better suited for post-commit change impact assessment.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (fivetran/great_expectations) · observed Aug 2, 2026
- GitHub forks (fivetran/great_expectations) · observed Aug 2, 2026
- Last push (fivetran/great_expectations) · observed Aug 2, 2026
- License file (Apache-2.0) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (InfuseAI/piperider) · observed Aug 3, 2026
- GitHub forks (InfuseAI/piperider) · observed Aug 3, 2026
- Last push (InfuseAI/piperider) · observed Jan 3, 2025
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: great_expectations 12k · piperider 495 (synced Aug 2, 2026).
Common questions
- What is the difference between great_expectations and piperider?
- great_expectations: Always know what to expect from your data. piperider: Code review for data in dbt. See the comparison table for live GitHub stats and shared categories.
- When should I choose great_expectations over piperider?
- Choose great_expectations over piperider when Requirements: Supports Python versions 3.10 through 3.13, with experimental support for Python 3.14 and later via an environment variable.; Tags unique to great_expectations: data-engineering, data-quality, mlops; When you need detailed and automated documentation for each set of validation results to simplify your data quality processes while preserving institutional knowledge.
- When should I choose piperider over great_expectations?
- Choose piperider over great_expectations when Requirements: Requires a pre-existing dbt project with defined connection profiles.; Must be installed through Python using the package manager pip and may need specific connectors based on data source.; Tags unique to piperider: code-review, continuous-integration, data-observability, data-profiling; Also covers Evaluation & Observability; piperider ships Docker support for self-hosted deployment; When working with dbt models where pre-merge data validation is essential to detect changes that impact downstream models.
- When should I avoid great_expectations?
- For environments that strictly require adherence to Python versions 3.9 or lower, since Great Expectations supports only 3.10 through 3.13 natively. If your data integration requirements are not compatible with those listed in the Great Expectations compatibility reference.
- When should I avoid piperider?
- Consider other tools if continuous support and active development are required, as PipeRider has been superseded by Recce and will no longer receive regular updates. Avoid using if your project requires real-time data testing or monitoring; PipeRider is better suited for post-commit change impact assessment.
- Is great_expectations or piperider more popular on GitHub?
- great_expectations has more GitHub stars (11,690 vs 495). Stars measure visibility, not whether either tool fits your constraints.
- Are great_expectations and piperider open source?
- Yes - both are open-source projects on GitHub (great_expectations: Apache-2.0, piperider: Apache-2.0).
- Where can I find alternatives to great_expectations or piperider?
- GraphCanon lists graph-backed alternatives at great_expectations alternatives and piperider alternatives (great_expectations markdown twin, piperider markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, great_expectations or piperider?
- great_expectations: Very active. piperider: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for great_expectations and piperider?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: great_expectations trust report; piperider trust report.