ML platform (SageMaker AI ↔ Azure ML)
Amazon SageMaker Canvas vs Azure ML automated ML (AutoML) / Azure ML Designer
SageMaker Canvas maps partially to the no-code AutoML UI and Designer in Azure Machine Learning studio.
Azure has no single analyst-focused product with the same scope.
Side-by-side comparison
| Aspect | Amazon Web Services | Microsoft Azure |
|---|---|---|
| Service | Amazon SageMaker Canvas | Azure ML automated ML (AutoML) Azure ML Designer |
| Lifecycle | Generally available | Generally available Classic prebuilt (v1) components get no new additions. Use custom (v2) components for new projects. |
| What it is | No-code ML for analysts. Tabular, time series, text, and image predictions, plus access to foundation models. | AutoML for classification, regression, forecasting, computer vision, and NLP, from code (SDK/CLI v2) or a no-code studio UI. Drag-and-drop pipeline builder. |
| Pricing model | Canvas bills a session charge per hour while logged in, plus training and prediction costs. | Billed for the compute AutoML and Designer jobs use. |
| Docs | Amazon SageMaker Canvas docs | Azure ML automated ML (AutoML) docs Azure ML Designer docs |
| Pricing page | Amazon SageMaker Canvas pricing | Azure ML automated ML (AutoML) pricing Azure ML Designer pricing |
| Exams | AIF-C01 MLA-C01 Retiring | AI-901 AI-300 |
Key differences
- Canvas bundles data prep, AutoML (tabular, time series, text, image), ready-to-use models (document, vision, language), and foundation-model chat in one analyst app. It's also the recommended path for Forecast customers.
- On Azure, analysts typically use the AutoML UI or Designer in Azure ML studio, or the Fabric Data Science and Power BI AI features. Those are separate products, not one app.
Pricing summary
Pricing models only. No prices are quoted because they change by region and over time.
- AWS
- Canvas bills a session charge per hour while logged in, plus training and prediction costs. Amazon SageMaker Canvas pricing →
- Azure
- Billed for the compute AutoML and Designer jobs use. Azure ML automated ML (AutoML) pricing → Azure ML Designer pricing →
Certification exam mapping
| Exam | Provider | Level | Status |
|---|---|---|---|
| AWS Certified AI Practitioner AIF-C01 | AWS | Foundational | current Italian and German versions retire after Oct 15, 2026 (per AWS cert page). |
| AWS Certified Machine Learning Engineer – Associate MLA-C01 | AWS | Associate | retiring Being updated to MLA-C02 (beta registration opened Sep 1, 2026). Last day for MLA-C01 in English was Sep 28, 2026; Korean, Japanese, and Simplified Chinese remain until MLA-C02 GA. |
| Microsoft Certified – Azure AI Fundamentals AI-901 | Azure | Fundamentals | current AI-901 replaces AI-900 for this certification (English version updated Apr 15, 2026). Covers Microsoft Foundry. |
| Microsoft Certified – Machine Learning Operations Engineer Associate AI-300 | Azure | Associate | current MLOps and GenAIOps infrastructure on Azure (IaC with Bicep/CLI, GitHub Actions). Closest successor in scope to the retired DP-100. |
Relevance is based on each exam's published scope, not a line-by-line objective match. Check the official study guide.
FAQ
What is the Azure equivalent of Amazon SageMaker Canvas?
SageMaker Canvas maps partially to the no-code AutoML UI and Designer in Azure Machine Learning studio. Azure has no single analyst-focused product with the same scope.
How does pricing compare between Amazon SageMaker Canvas and Azure ML automated ML (AutoML) and Azure ML Designer?
AWS: Canvas bills a session charge per hour while logged in, plus training and prediction costs. Azure: Billed for the compute AutoML and Designer jobs use. Check the official pricing pages for current rates.
Which certification exams cover this topic?
AWS Certified AI Practitioner (AIF-C01); AWS Certified Machine Learning Engineer – Associate (MLA-C01) [retiring]; Microsoft Certified – Azure AI Fundamentals (AI-901); Microsoft Certified – Machine Learning Operations Engineer Associate (AI-300).