Machine Learning & Data Science · head to head
BigQuery ML vs Azure Machine Learning
BigQuery ML
Machine Learning & Data Science
Machine learning in BigQuery using SQL
- From
- Free
- Rated
- -
Azure Machine Learning
Machine Learning & Data Science
Enterprise-grade machine learning service
- From
- Free
- Rated
- -
The short version
- Each has a real cost: BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it; Azure Machine Learning requires knowledge of Azure ecosystem and integration with other Azure services
- They diverge on capability: BigQuery ML covers SQL-based ML, Azure Machine Learning covers Automated ML.
Where they differ
Only the attributes on which BigQuery ML and Azure Machine Learning actually diverge.
| Attribute | BigQuery ML | Azure Machine Learning |
|---|---|---|
| Platforms | Web | Azure Cloud |
| Founded | 2008 | 1975 |
Identical on both: starting price (Free), pricing model (usage-based), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in BigQuery ML
- SQL-based ML
- AutoML Tables
- Model export
- Prediction functions
- Feature preprocessing
- BigQuery
- Vertex AI
- TensorFlow
Only in Azure Machine Learning
- Automated ML
- Designer (drag-and-drop)
- Notebooks
- MLOps
- Model registry
- Azure Blob Storage
- Azure DevOps
- Power BI
Both cover
- Web support
What people use each for
The jobs each tool is most often brought in to do.
BigQuery ML
- Training models in SQL without exporting datanot Azure Machine Learning
- Linear and logistic regression on warehouse datanot Azure Machine Learning
- K-means clustering and matrix factorisation for recommendationsnot Azure Machine Learning
- Time series forecasting with ARIMA_PLUSnot Azure Machine Learning
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Azure Machine Learning
Azure Machine Learning
- Machine learningnot BigQuery ML
- Data analysisnot BigQuery ML
- Model trainingnot BigQuery ML
- Predictive analyticsnot BigQuery ML
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
BigQuery ML
- Not available in BigQuery's Standard edition, so the cheapest tier cannot use it
- Billed through BigQuery compute and storage rather than as its own product, so training cost tracks data scanned
- Remote models incur extra Agent Platform charges on top
- Externally trained model types such as boosted trees and AutoML run through Agent Platform rather than inside BigQuery
Azure Machine Learning
- Requires knowledge of Azure ecosystem and integration with other Azure services
- Compute resources for training and inference generate separate charges
Pricing, plan by plan
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
Azure Machine Learning
Free- Free TierFree
- Limited compute
- Basic features
- Pay-as-you-go$0.05/hour
- Full platform
- All compute options
- Enterprise features
Which should you pick?
Choose BigQuery ML if
- You need sql-based ml.
- You want to start without paying.
- You also want automl tables.
Choose Azure Machine Learning if
- You need automated ml.
- You want to start without paying.
- You work on Azure Cloud.
- You also want designer (drag-and-drop).
Questions people ask
- Is BigQuery ML or Azure Machine Learning better?
- Neither clearly leads. BigQuery ML starts at Free and Azure Machine Learning at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, BigQuery ML or Azure Machine Learning?
- BigQuery ML starts at Free and Azure Machine Learning at Free.
- Does BigQuery ML or Azure Machine Learning run on more platforms?
- BigQuery ML runs on Web. Azure Machine Learning runs on Azure Cloud.
- Can I use BigQuery ML for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is BigQuery ML best used for?
- BigQuery ML is most often used for training models in sql without exporting data, linear and logistic regression on warehouse data, k-means clustering and matrix factorisation for recommendations, time series forecasting with arima_plus. Of those, training models in sql without exporting data and linear and logistic regression on warehouse data are not what Azure Machine Learning is typically brought in for.
- What can BigQuery ML do that Azure Machine Learning cannot?
- BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Azure Machine Learning covers Automated ML, Designer (drag-and-drop), Notebooks, MLOps. Both handle Web support.
Answered from the vendors’ own pages
Azure Machine Learning: Does Azure Machine Learning have any platform licensing fees?
No, Azure Machine Learning carries no extra cost. You only pay for the underlying compute resources utilized during model training or inference.
SourceAzure Machine Learning: What AutoML capabilities does Azure Machine Learning provide?
Azure Machine Learning supports automated model creation for classification, regression, vision, and natural language processing tasks.
SourceAzure Machine Learning: Does Azure ML support language model fine-tuning?
Yes, Azure Machine Learning supports fine-tuning of foundation models from providers including OpenAI, Meta, Hugging Face, and Cohere.
SourceAzure Machine Learning: What MLOps features are included?
Azure ML includes end-to-end pipeline automation with CI/CD capabilities, managed endpoints for model deployment, and monitoring tools.
SourceAzure Machine Learning: Can I access foundation models from multiple vendors?
Yes, Azure Machine Learning provides access to a model catalog with foundation models from Microsoft, OpenAI, Hugging Face, Meta, and Cohere.
Source