Google Cloud → AWS and Azure
AWS and Azure equivalents of BigQuery ML
The closest AWS equivalents of Google Cloud BigQuery ML are Amazon SageMaker Unified Studio, Amazon SageMaker Canvas, Amazon Forecast and Amazon Lookout for Metrics; on Azure, Microsoft Fabric Data Science, Azure Machine Learning, Azure ML automated ML (AutoML), Azure ML Designer and Azure AI Metrics Advisor.
About BigQuery ML
| Provider | Google Cloud |
|---|---|
| Status | Generally available |
| What it is | Create and run ML models with SQL inside BigQuery, including forecasting (ARIMA_PLUS, TimesFM), anomaly detection, and calls to remote Gemini models. |
| Documentation | docs.cloud.google.com |
| Pricing | Official pricing page |
Mappings (4)
| Capability | AWS | Match (GCP vs AWS) | Azure |
|---|---|---|---|
| Unified data + analytics + AI workspace | Amazon SageMaker Unified Studio | Partial match | Microsoft Fabric Data Science, Azure Machine Learning |
| No-code ML for analysts | Amazon SageMaker Canvas | Partial match | Azure ML automated ML (AutoML), Azure ML Designer |
| Time-series forecasting | Amazon Forecast Maintenance, Amazon SageMaker Canvas | Direct match | Azure ML automated ML (AutoML) |
| Business-metric anomaly detection | Amazon Lookout for Metrics Retired | Partial match | Azure AI Metrics Advisor Retired |
Unified data + analytics + AI workspace Partial match
SageMaker Unified Studio has no single Google Cloud counterpart. The closest experience is BigQuery (SQL, BigQuery ML, data governance) with Colab Enterprise notebooks opened from BigQuery, connected to Agent Platform.
- Colab Enterprise notebooks can be created directly from the BigQuery editor.
- Data, analytics, and ML stay separate products in one console rather than one project-based studio.
No-code ML for analysts Partial match
SageMaker Canvas has no direct counterpart. Agent Platform AutoML has a console workflow, and BigQuery ML lets analysts train models with SQL.
- Neither is a spreadsheet-style, business-analyst app like Canvas.
- Gemini in BigQuery can help write SQL and BigQuery ML statements.
Time-series forecasting Direct match
Amazon Forecast (in maintenance) maps to Agent Platform tabular forecasting and to BigQuery ML forecasting (ARIMA_PLUS and the TimesFM foundation model).
- TimesFM is pretrained, so AI.FORECAST forecasts from SQL without training your own model.
- Forecast is closed to new customers on AWS; SageMaker Canvas is the AWS path.
Business-metric anomaly detection Partial match
Lookout for Metrics (discontinued) maps partly to BigQuery ML anomaly detection on time-series data in BigQuery.
- You write SQL (for example AI.DETECT_ANOMALIES) instead of configuring a managed detector with alerts.