--- title: "great_expectations vs lux" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/fivetran-great-expectations-vs-lux-org-lux" tools: ["fivetran-great-expectations", "lux-org-lux"] --- # great_expectations vs lux *GraphCanon updated Aug 3, 2026* ## Verdict Pick great_expectations if great Expectations is a Python library that helps maintain data quality through unit testing mechanisms known as expectations; pick lux if automatically visualize pandas dataframes to reveal trends. [great_expectations](https://docs.greatexpectations.io/) reports 12k GitHub stars, 1.8k forks, and 39 open issues, last pushed Aug 2, 2026. [lux](https://github.com/lux-org/lux) has 5.4k stars, 379 forks, and 90 open issues, last pushed Mar 20, 2024. Figures are from public GitHub metadata via [great_expectations's repository](https://github.com/fivetran/great_expectations) and [lux's repository](https://github.com/lux-org/lux). | | [great_expectations](/tools/fivetran-great-expectations.md) | [lux](/tools/lux-org-lux.md) | | --- | --- | --- | | Tagline | Always know what to expect from your data | Automatically visualize pandas dataframes. | | Stars | 11,690 | 5,375 | | Forks | 1,790 | 379 | | Open issues | 39 | 90 | | Language | Python | Python | | Adopt for | Great Expectations is a Python library that helps maintain data quality through unit testing mechanisms known as expectations. | Automatically visualize pandas dataframes to reveal trends. | | Persona | - | - | | Runtime | - | - | | License | Great Expectations is available under the Apache-2.0 license. | Apache-2.0 | | Categories | Data & Retrieval | Data & Retrieval, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [great_expectations](/tools/fivetran-great-expectations.md) | [lux](/tools/lux-org-lux.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 865d | | Open issues (now) | 39 | 90 | | Full report | [trust report](/tools/fivetran-great-expectations/trust.md) | [trust report](/tools/lux-org-lux/trust.md) | ## Shared compatibility - **Python**: [great_expectations](/tools/fivetran-great-expectations.md) - Python runtime; [lux](/tools/lux-org-lux.md) - Python runtime ## Decision facts: great_expectations - **Requirements:** Supports Python versions 3.10 through 3.13, with experimental support for Python 3.14 and later via an environment variable. - **Adopt for:** Great Expectations is a Python library that helps maintain data quality through unit testing mechanisms known as expectations. - **License detail:** Great Expectations is available under the Apache-2.0 license. ## Decision facts: lux - **Adopt for:** Automatically visualize pandas dataframes to reveal trends. ## Choose when ### 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. ### Choose lux if… - Tags unique to lux: data-science, jupyter, pandas, python. - Also covers Developer Tools. - When you need quick insights from pandas dataframes without manual visualization setup. ## 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. ## When NOT to use lux - Avoid if your workflow strictly avoids third-party extensions for Pandas. - Not suitable when detailed customization of visualizations is required, as Lux focuses on automated recommendations. ## Common questions ### What is the difference between great_expectations and lux? great_expectations: Always know what to expect from your data. lux: Automatically visualize pandas dataframes.. See the comparison table for live GitHub stats and shared categories. ### When should I choose great_expectations over lux? Choose great_expectations over lux 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 lux over great_expectations? Choose lux over great_expectations when Tags unique to lux: data-science, jupyter, pandas, python; Also covers Developer Tools; When you need quick insights from pandas dataframes without manual visualization setup. ### 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 lux? Avoid if your workflow strictly avoids third-party extensions for Pandas. Not suitable when detailed customization of visualizations is required, as Lux focuses on automated recommendations. ### Is great_expectations or lux more popular on GitHub? great_expectations has more GitHub stars (11,690 vs 5,375). Stars measure visibility, not whether either tool fits your constraints. ### Are great_expectations and lux open source? Yes - both are open-source projects on GitHub (great_expectations: Apache-2.0, lux: Apache-2.0). ### Where can I find alternatives to great_expectations or lux? GraphCanon lists graph-backed alternatives at [great_expectations alternatives](/tools/fivetran-great-expectations/alternatives) and [lux alternatives](/tools/lux-org-lux/alternatives) ([great_expectations markdown twin](/tools/fivetran-great-expectations/alternatives.md), [lux markdown twin](/tools/lux-org-lux/alternatives.md)), 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](/compare/fivetran-great-expectations-vs-lux-org-lux.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, great_expectations or lux? great_expectations: Very active. lux: 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 lux? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [great_expectations trust report](/tools/fivetran-great-expectations/trust); [lux trust report](/tools/lux-org-lux/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=fivetran-great-expectations`](/api/graphcanon/graph?tool=fivetran-great-expectations) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_