The Best AutoML Software in 2026
We researched AutoML software using official vendor websites, including pricing pages, plan tables, and product documentation. Rankings reflect each platform’s performance on the category’s core job, value for money, and verified features for automating model selection, feature engineering, training, and evaluation.
Our top picks
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Top ranked
SAS Viya#1 of 299.3/10A broad, governed AutoML platform for complex enterprise and regulated workloads.
Pricing on request · 14-day trial
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Runner-up
DataRobot#2 of 299.1/10A focused enterprise AutoML platform with forecasting, deployment, monitoring, and governance.
Pricing on request · 30-day trial
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Top-ranked free plan
IBM Watson Studio#3 of 299.0/10A broad AutoML workspace for teams that need collaboration, deployment and governance.
Free plan
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.
The full ranking 29 tools, best first
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Best forGoverned enterprise and regulated workloads
A broad, governed AutoML platform for complex enterprise and regulated workloads.
Pricing on request · 14-day trial Our SAS Viya verdict → Visit SAS ViyaFor vendors Sponsor this spot · #1 · $149/mo →9.3/10★★★★★Visit SAS Viya -
Best forTeams wanting focused enterprise AutoML
A focused enterprise AutoML platform with forecasting, deployment, monitoring, and governance.
Pricing on request · 30-day trial Our DataRobot verdict → Visit DataRobotFor vendors Sponsor this spot · #2 · $99/mo →9.1/10★★★★★Visit DataRobot -
Best forTeams seeking affordable collaborative AutoML
A broad AutoML workspace for teams that need collaboration, deployment and governance.
9.0/10★★★★☆Visit site -
Best forPractitioners needing deep automated modeling
Deep automated modeling with forecasting, interpretability, deployment, and custom recipes.
Pricing on request · 21-day trial Our H2O Driverless AI verdict → Visit H2O.aiFor vendors Sponsor this spot · #4 · $69/mo →8.9/10★★★★☆Visit H2O.ai -
Best forAWS users needing managed AutoML execution
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
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
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
A broad AutoML platform for marketing prediction workflows and operational delivery.
8.5/10★★★★☆Visit Pecan AI -
Best forTeams wanting priced, API-first AutoML
API-first AutoML with forecasting, explainability, automation, and flexible deployment options.
8.4/10★★★★☆Visit BigML -
Best forDevelopers wanting broad open-source AutoML
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
A Python-first AutoML library for automated modeling, forecasting, and batch deployment.
8.2/10★★★★☆Visit AutoGluon -
Best forDevelopers needing flexible open-source search
A flexible Python library for automated model search across diverse ML tasks.
8.1/10★★★★☆Visit FLAML -
Best forResearchers building multimodal pipelines
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
A capable open-source Python AutoML package for explainable tabular modeling.
7.9/10★★★★☆Visit MLJAR -
Best forTeams handling tabular, text, and image data
A flexible open-source AutoML framework for tabular, text, and image workflows.
- Model explainability
- Feature engineering
- Automated model selection
7.8/10★★★★☆Visit LightAutoML -
Best forPyTorch developers needing automated search
A free, code-first AutoML toolkit for PyTorch search, tuning, preprocessing, and ensembles.
- Feature engineering
- Automated model selection
7.7/10★★★★☆Visit Auto-PyTorch -
Best forSmall teams wanting no-code predictive models
A no-code AutoML platform for building, deploying, and monitoring predictive models.
7.6/10★★★★☆Visit Obviously AI -
Best forScientific teams needing interpretable AutoML
A focused AutoML workspace for scientific teams that need explainable models.
- Model explainability
- Feature engineering
- Automated model selection
7.5/10★★★★☆Visit JADBio -
Best forPython teams prioritizing data-quality checks
A code-first AutoML library for Python teams that need automated search and data-quality checks.
- Model explainability
- Feature engineering
- Automated model selection
7.4/10★★★★☆Visit EvalML -
Best forLinux developers optimizing classical ML
A focused AutoML toolkit for Linux developers optimizing classical ML.
7.3/10★★★★☆Visit auto-sklearn -
Best forResearchers exploring genetic pipeline optimization
A focused, free AutoML tool for researchers optimizing supervised-learning pipelines.
7.2/10★★★★☆Visit TPOT -
Best forDevelopers composing validated ML pipelines
A code-first AutoML library for composing and validating scikit-learn-compatible pipelines.
- Automated model selection
7.1/10★★★★☆Visit Lale -
Best forDevelopers automating Keras model search
A code-first AutoML library for automating Keras model search across common data types.
- Feature engineering
- Automated model selection
7.0/10★★★★☆Visit AutoKeras -
Best forSmall teams optimizing tabular ML pipelines
A code-first, self-hosted AutoML package for tabular classification and regression.
- Automated model selection
6.9/10★★★☆☆Visit GAMA -
Best forBusiness users exploring no-code predictions
No-code predictive modeling and campaign analytics for business teams.
6.8/10★★★☆☆Visit Akkio -
Best forTeams hosting notebook environments on Kubernetes
A capable Kubernetes notebook layer, but not a focused AutoML platform.
6.7/10★★★☆☆Explore Kubeflow -
Best forOracle users needing managed ML notebooks
A capable hosted notebook environment for Oracle-centered analytics teams, not a dedicated AutoML suite.
6.6/10★★★☆☆Visit Oracle -
Best forTeams needing managed online feature serving
A cloud feature store for offline-to-online ML workflows, not a full AutoML system.
6.4/10★★★☆☆Visit Alibaba Cloud -
Best forDevelopers needing vector similarity search
A cloud vector-search service for developers building similarity-driven AI applications.
6.3/10★★★☆☆Visit Google Cloud
No tools match those filters.
Compare at a glance
| # | Tool | Free plan | Paid from | Score |
|---|---|---|---|---|
| 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 | |
| 16 | Auto-PyTorch | Yes | Free | 7.7 |
| 17 | Obviously AI | Yes | 7.6 | |
| 18 | JADBio | Yes | $2,199/mo | 7.5 |
| 19 | EvalML | Yes | Free | 7.4 |
| 20 | auto-sklearn | Free | 7.3 | |
| 21 | TPOT | Yes | Free | 7.2 |
| 22 | Lale | Yes | Free | 7.1 |
| 23 | AutoKeras | Free | 7.0 | |
| 24 | GAMA | Yes | Free | 6.9 |
| 25 | Akkio | Yes | 6.8 | |
| 26 | Kubeflow Notebooks | Free | 6.7 | |
| 27 | Oracle Machine Learning Notebooks | No | 6.6 | |
| 28 | Alibaba Cloud PAI FeatureStore | No | $0.00026/GB usage-based | 6.4 |
| 29 | Vertex AI Vector Search | 6.3 |
Head-to-head All 22 comparisons →
- SAS Viya vs Amazon SageMaker Autopilot
- SAS Viya vs dotData Enterprise
- SAS Viya vs Altair AI Studio
- SAS Viya vs Pecan AI
- DataRobot vs Amazon SageMaker Autopilot
- DataRobot vs dotData Enterprise
- DataRobot vs Altair AI Studio
- DataRobot vs Pecan AI
- IBM Watson Studio vs Amazon SageMaker Autopilot
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How we rank AutoML software
Every tool on this page was researched by iTechGuides Editors from its official website — pricing pages, plan tables and product documentation. We rank on how well each one does this category's core job, what the free or entry plan includes, and where it falls short. Where we have enough verified facts, the score out of 10 is a rubric — job fit, value and how much we could verify — shown with its breakdown on every tool's page; a tool we have not verified enough to score yet shows its rank without a number. Scores are re-checked when a product changes its plans. Read the full editorial policy, or submit a tool we missed.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Last updated · How we research and update