Best GAMA Alternatives in 2026
The top GAMA alternatives are SAS Viya, DataRobot and IBM Watson Studio: 15 AutoML software our editors would look at instead of GAMA, in our ranking order.
GAMA: A code-first, self-hosted AutoML package for tabular classification and regression. Where it falls short: focused on tabular classification and regression.
Switching from GAMA? For most automl software buyers the best GAMA alternative is SAS Viya, built for governed enterprise and regulated workloads. IBM Watson Studio has a free plan.
Why People Look for a GAMA Alternative
- Focused on tabular classification and regression
- Uses a code-based workflow rather than a dashboard
- Community support; the dashboard is temporarily disabled
- No feature engineering — 4 of the alternatives below have it
- No model explainability — 4 of the alternatives below have it
Quick Picks by What You Need
- Best overallSAS Viya9.3
Governed enterprise and regulated workloads
Visit SAS Viya - Best free optionIBM Watson Studio9.0
Has a free plan
Visit IBM Watson Studio - Best for feature engineeringAmazon SageMaker Autopilot8.8
Feature engineering (GAMA: no)
Visit Amazon SageMaker Autopilot
All 15 GAMA Alternatives, Ranked
Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.
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Best forGoverned enterprise and regulated workloads
- Better than GAMA:
- Editor score 9.3 vs 6.9
A broad, governed AutoML platform for complex enterprise and regulated workloads.
9.3/10★★★★★Visit SAS Viya -
Best forTeams wanting focused enterprise AutoML
- Better than GAMA:
- Editor score 9.1 vs 6.9
A focused enterprise AutoML platform with forecasting, deployment, monitoring, and governance.
9.1/10★★★★★Visit DataRobot -
Best forTeams seeking affordable collaborative AutoML
- Better than GAMA:
- Editor score 9.0 vs 6.9
A broad AutoML workspace for teams that need collaboration, deployment and governance.
9.0/10★★★★☆Visit site -
Best forPractitioners needing deep automated modeling
- Better than GAMA:
- Editor score 8.9 vs 6.9
Deep automated modeling with forecasting, interpretability, deployment, and custom recipes.
8.9/10★★★★☆Visit H2O.ai -
Best forAWS users needing managed AutoML execution
- Better than GAMA:
- Feature engineering
- Model explainability
- Editor score 8.8 vs 6.9
A broad, AWS-native AutoML workflow with usage-based pricing and vendor-cloud limits.
- Model explainability
- Feature engineering
- Automated model selection
8.8/10★★★★☆Visit AWS -
Best forEnterprises automating feature discovery
- Better than GAMA:
- Feature engineering
- Model explainability
- Editor score 8.7 vs 6.9
Enterprise AutoML for automated feature discovery, modeling, deployment, and monitoring.
- Model explainability
- Feature engineering
- Automated model selection
8.7/10★★★★☆Visit dotData -
Best forVisual AutoML users with a free option
- Better than GAMA:
- Editor score 8.6 vs 6.9
A visual AutoML workspace with forecasting, coding support, and local or hub-based execution.
8.6/10★★★★☆Visit Altair -
Best forMarketing teams needing predictive workflows
- Better than GAMA:
- Editor score 8.5 vs 6.9
A broad AutoML platform for marketing prediction workflows and operational delivery.
8.5/10★★★★☆Visit Pecan AI -
Best forTeams wanting priced, API-first AutoML
- Better than GAMA:
- Editor score 8.4 vs 6.9
API-first AutoML with forecasting, explainability, automation, and flexible deployment options.
8.4/10★★★★☆Visit BigML -
Best forDevelopers wanting broad open-source AutoML
- Better than GAMA:
- Editor score 8.3 vs 6.9
A free, broad AutoML platform with APIs, clients, connectors, and model export.
8.3/10★★★★☆Visit H2O.ai -
Best forPython teams needing open-source forecasting
- Better than GAMA:
- Editor score 8.2 vs 6.9
A Python-first AutoML library for automated modeling, forecasting, and batch deployment.
8.2/10★★★★☆Visit AutoGluon -
Best forDevelopers needing flexible open-source search
- Better than GAMA:
- Editor score 8.1 vs 6.9
A flexible Python library for automated model search across diverse ML tasks.
8.1/10★★★★☆Visit FLAML -
Best forResearchers building multimodal pipelines
- Better than GAMA:
- Feature engineering
- Model explainability
- Editor score 8.0 vs 6.9
A code-first AutoML framework for researchers working across tables, text, and images.
- Model explainability
- Feature engineering
- Automated model selection
8.0/10★★★★☆Visit FEDOT -
Best forPython users wanting explainable open-source AutoML
- Better than GAMA:
- Editor score 7.9 vs 6.9
A capable open-source Python AutoML package for explainable tabular modeling.
7.9/10★★★★☆Visit MLJAR -
Best forTeams handling tabular, text, and image data
- Better than GAMA:
- Feature engineering
- Model explainability
- Editor score 7.8 vs 6.9
A flexible open-source AutoML framework for tabular, text, and image workflows.
- Model explainability
- Feature engineering
- Automated model selection
7.8/10★★★★☆Visit LightAutoML
GAMA Alternatives: Common Questions
What is the best alternative to GAMA?
SAS Viya: #1 in our AutoML Software ranking, with an editor score of 9.3 out of 10. A broad, governed AutoML platform for complex enterprise and regulated workloads.
Is there a free alternative to GAMA?
Yes. IBM Watson Studio, Altair AI Studio, BigML, H2O-3 and AutoGluon have a free plan or a free tier (9 of the 15 alternatives on this page).
Why do people look for GAMA alternatives?
Focused on tabular classification and regression; Uses a code-based workflow rather than a dashboard; Community support; the dashboard is temporarily disabled.
How do I switch from GAMA?
Export your data from GAMA (most tools have an export in their settings). Sign up for the alternative; start on its free plan or trial if it has one. Import your export and set up the integrations your team relies on. Run both side by side for a short while, then cancel GAMA.
How to Switch from GAMA
- Export your data from GAMA (most tools have an export in their settings).
- Sign up for the alternative; start on its free plan or trial if it has one.
- Import your export and set up the integrations your team relies on.
- Run both side by side for a short while, then cancel GAMA.
GAMA vs Each Alternative
| # | Tool | Free plan | Paid from | Score |
|---|---|---|---|---|
| 24 | GAMA | Yes | Free | 6.9 |
| 1 | SAS Viya | No | 9.3 | |
| 2 | DataRobot | 9.1 | ||
| 3 | IBM Watson Studio | Yes | 9.0 | |
| 4 | H2O Driverless AI | No | 8.9 | |
| 5 | Amazon SageMaker Autopilot | No | 8.8 | |
| 6 | dotData Enterprise | 8.7 | ||
| 7 | Altair AI Studio | Yes | 8.6 | |
| 8 | Pecan AI | 8.5 | ||
| 9 | BigML | Yes | $10,000/yr | 8.4 |
| 10 | H2O-3 | Yes | Free | 8.3 |
| 11 | AutoGluon | Free | 8.2 | |
| 12 | FLAML | Yes | Free | 8.1 |
| 13 | FEDOT | Free | 8.0 | |
| 14 | MLJAR AutoML | Free | 7.9 | |
| 15 | LightAutoML | Free | 7.8 |
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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