Comparison
featuretools vs automl-gs
Verdict
Pick featuretools if a Python library dedicated to automating feature engineering processes designed to craft features from complex datasets that are interpretable and potentially boost the accuracy of machine learning models; pick automl-gs if automl-gs: Python tool for automated machine-learning model creation from CSV data.
Markdown twin · featuretools alternatives · automl-gs alternatives
GraphCanon updated Sep 30, 2026
12views this month
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Trust & integrity
| Signal | featuretools | automl-gs |
|---|---|---|
| Maintenance | Active (16d since push) As of Sep 28, 2026 · github_public_v1 | Dormant (2534d since push) As of Sep 30, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 28, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 30, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | Published findings As of Jul 11, 2026 · 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
- featuretools
- An open source python library for automated feature engineering
- automl-gs
- Automatically generate machine-learning models and code with input CSV and target field
Stars
- featuretools
- 7.7k
- automl-gs
- 1.9k
Forks
- featuretools
- 915
- automl-gs
- 178
Open issues
- featuretools
- 171
- automl-gs
- 28
Language
- featuretools
- Python
- automl-gs
- Python
Adopt for
- featuretools
- A Python library dedicated to automating feature engineering processes designed to craft features from complex datasets that are interpretable and potentially boost the accuracy of machine learning models.
- automl-gs
- automl-gs: Python tool for automated machine-learning model creation from CSV data
Persona
- featuretools
- -
- automl-gs
- -
Runtime
- featuretools
- -
- automl-gs
- -
License
- featuretools
- BSD-3-Clause
- automl-gs
- MIT
Last pushed
- featuretools
- Sep 11, 2026
- automl-gs
- Oct 22, 2019
Categories
- featuretools
- Model Training
- automl-gs
- Data & Retrieval, Model Training
Trust and health
Maintenance
- featuretools
- Active (82%)
- automl-gs
- Dormant (18%)
Days since push
- featuretools
- 16d
- automl-gs
- 2534d
Open issues (now)
- featuretools
- 171
- automl-gs
- 28
Stars delta
- featuretools
- +18 (30d)
- automl-gs
- -2 (30d)
Open issues delta
- featuretools
- +3 (30d)
- automl-gs
- 0 (30d)
Owner type
- featuretools
- Organization
- automl-gs
- User
OSV dependency advisories
- featuretools
- No lockfile (source not queried)
- automl-gs
- Published findings
Full report
- featuretools
- Trust report
- automl-gs
- Trust report
Choose featuretools if…
- License: featuretools is BSD-3-Clause, automl-gs is MIT.
- Tags unique to featuretools: automated-feature-engineering, feature-engineering.
- When the goal is to create high-quality features in a semi-automated manner using prior knowledge of relationships within data, enhancing interpretability of machine learning models
When NOT to use featuretools
- If a project requires extremely lightweight solutions that avoid dependencies and overheads associated with complex library packages
- In settings where the underlying data lacks clear relational structure, as Featuretools excels when data relationships are well-defined and can be exploited
Choose automl-gs if…
- License: automl-gs is MIT, featuretools is BSD-3-Clause.
- Tags unique to automl-gs: keras, machine-learning, python, tensorflow.
- Also covers Data & Retrieval.
- Need to rapidly prototype models with limited ML expertise
When NOT to use automl-gs
- Complex feature engineering or non-standard data inputs required
- Sensitive about licensing of the generated code
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (alteryx/featuretools) · observed Sep 28, 2026
- GitHub forks (alteryx/featuretools) · observed Sep 28, 2026
- Last push (alteryx/featuretools) · observed Sep 11, 2026
- License file (BSD-3-Clause) · observed Sep 28, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (minimaxir/automl-gs) · observed Sep 30, 2026
- GitHub forks (minimaxir/automl-gs) · observed Sep 30, 2026
- Last push (minimaxir/automl-gs) · observed Oct 22, 2019
- License file (MIT) · observed Sep 30, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: featuretools 7.7k · automl-gs 1.9k (synced Sep 28, 2026).
Common questions
- What is the difference between featuretools and automl-gs?
- featuretools: An open source python library for automated feature engineering. automl-gs: Automatically generate machine-learning models and code with input CSV and target field. See the comparison table for live GitHub stats and shared categories.
- When should I choose featuretools over automl-gs?
- Choose featuretools over automl-gs when License: featuretools is BSD-3-Clause, automl-gs is MIT; Tags unique to featuretools: automated-feature-engineering, feature-engineering; When the goal is to create high-quality features in a semi-automated manner using prior knowledge of relationships within data, enhancing interpretability of machine learning models.
- When should I choose automl-gs over featuretools?
- Choose automl-gs over featuretools when License: automl-gs is MIT, featuretools is BSD-3-Clause; Tags unique to automl-gs: keras, machine-learning, python, tensorflow; Also covers Data & Retrieval; Need to rapidly prototype models with limited ML expertise.
- When should I avoid featuretools?
- If a project requires extremely lightweight solutions that avoid dependencies and overheads associated with complex library packages In settings where the underlying data lacks clear relational structure, as Featuretools excels when data relationships are well-defined and can be exploited
- When should I avoid automl-gs?
- Complex feature engineering or non-standard data inputs required Sensitive about licensing of the generated code
- Is featuretools or automl-gs more popular on GitHub?
- featuretools has more GitHub stars (7,683 vs 1,867). Stars measure visibility, not whether either tool fits your constraints.
- Are featuretools and automl-gs open source?
- Yes - both are open-source projects on GitHub (featuretools: BSD-3-Clause, automl-gs: MIT).
- Where can I find alternatives to featuretools or automl-gs?
- GraphCanon lists graph-backed alternatives at featuretools alternatives and automl-gs alternatives (featuretools markdown twin, automl-gs 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, featuretools or automl-gs?
- featuretools: Active. automl-gs: 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 featuretools and automl-gs?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: featuretools trust report; automl-gs trust report.