kitio.aiAmazon SageMaker vs Azure Machine Learning
A side-by-side look at pricing plans, free tiers, features, pros and cons, updated for 2026. Amazon SageMaker starts at See pricing page and Azure Machine Learning starts at See pricing page. Check both pricing pages for current plans.
At a glance
Best for
Category
Pricing model
Starting price
Free plan
Made by
Based in
Rating
Key features
- Model training and hosting
- Unified Studio
- Lakehouse architecture
- Data and AI governance
- Data agent
- Bedrock integration
- AutoML
- Drag-and-drop designer
- Managed compute and endpoints
- Model registry
- MLflow tracking
- Prompt flow
| Feature | Amazon SageMaker | Azure Machine Learning |
|---|---|---|
| Best for | AWS platform for building, training and deploying ML and AI models | Microsoft's cloud platform for training, deploying and managing ML models |
| Category | Models & APIs | Models & APIs |
| Pricing model | Paid | Paid |
| Starting price | See pricing page | See pricing page |
| Free plan | No | No |
| Made by | Amazon Web Services | Microsoft |
| Based in | United States | United States |
| Rating | No ratings yet | No ratings yet |
| Key features |
|
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Pricing compared
Amazon SageMaker starts at See pricing page and Azure Machine Learning starts at See pricing page. Check both pricing pages for current plans.
Free plan
Cheapest paid plan
Top plan
Free trial
2 plans
Pay as you go
Varies by service
- Billed per resource used
- Small monthly free allowances
Data Agent
$0.04 / credit
- Agent usage billed in credits
Prices in USD, checked Nov 5, 2026 or later. Plans change often, so confirm on each tool's site before you buy.
Pros and cons
Amazon SageMaker
- Covers the full ML lifecycle
- Deep integration with other AWS services
- Pay only for what you use
- Usage pricing is hard to predict
- Steep learning curve for newcomers
- Ties your stack to AWS
Azure Machine Learning
- Covers the full model lifecycle
- Code-first and low-code options
- Strong enterprise security on Azure
- Compute costs are hard to predict
- Steep learning curve for newcomers
- Tied to the Azure ecosystem
Which one should you choose?
Choose Amazon SageMaker if you want:
- Covers the full ML lifecycle
- Deep integration with other AWS services
- Pay only for what you use
Watch out: usage pricing is hard to predict.
Choose Azure Machine Learning if you want:
- Covers the full model lifecycle
- Code-first and low-code options
- Strong enterprise security on Azure
Watch out: compute costs are hard to predict.
Amazon SageMaker vs Azure Machine Learning FAQ
What is the difference between Amazon SageMaker and Azure Machine Learning?
Amazon SageMaker: AWS platform for building, training and deploying ML and AI models. Azure Machine Learning: Microsoft's cloud platform for training, deploying and managing ML models. Both are models & apis tools.
Is Amazon SageMaker or Azure Machine Learning cheaper?
Amazon SageMaker starts at See pricing page and Azure Machine Learning starts at See pricing page. Check both pricing pages for current plans.
Do Amazon SageMaker and Azure Machine Learning have free plans?
Amazon SageMaker: No. Azure Machine Learning: No.
Who makes Amazon SageMaker?
Amazon SageMaker is made by Amazon Web Services, based in United States.
Who makes Azure Machine Learning?
Azure Machine Learning is made by Microsoft, based in United States.
Which should I choose, Amazon SageMaker or Azure Machine Learning?
Choose Amazon SageMaker if you value covers the full ml lifecycle and deep integration with other aws services. Choose Azure Machine Learning if you value covers the full model lifecycle and code-first and low-code options.