Software · head to head
SAS vs BigQuery ML
The short version
- Each has a real cost: SAS sAS publishes no rate, no minimum and no named cost driver; the how to buy page offers only a customized price quote based on your requirements and deployment preferences; BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it
- They diverge on capability: SAS covers Statistical analysis, BigQuery ML covers SQL-based ML.
Where they differ
Only the attributes on which SAS and BigQuery ML actually diverge.
| Attribute | SAS | BigQuery ML |
|---|---|---|
| Pricing model | subscription | usage-based |
| Platforms | Linux, Windows, Web | Web |
| Founded | 1976 | 2008 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).
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 SAS
- Statistical analysis
- Machine learning
- Forecasting
- Text analytics
- Optimization
- Python
- R
- Hadoop
Only in BigQuery ML
- SQL-based ML
- AutoML Tables
- Model export
- Prediction functions
- Feature preprocessing
- BigQuery
- Vertex AI
- TensorFlow
Both cover
- Web support
What people use each for
The jobs each tool is most often brought in to do.
SAS
- Regulated statistical analysis and clinical reportingnot BigQuery ML
- Enterprise data management, visualization and decisioning on one licensed platformnot BigQuery ML
BigQuery ML
- Training models in SQL without exporting datanot SAS
- Linear and logistic regression on warehouse datanot SAS
- K-means clustering and matrix factorisation for recommendationsnot SAS
- Time series forecasting with ARIMA_PLUSnot SAS
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot SAS
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
SAS
- SAS publishes no rate, no minimum and no named cost driver; the how to buy page offers only a customized price quote based on your requirements and deployment preferences
- Most new and existing customers are routed through authorized resellers rather than buying direct
- Cloud marketplace purchases require choosing between pay as you go and bring your own licence, each with different licensing terms
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
Pricing, plan by plan
SAS
Free- SAS OnDemand for AcademicsFree
- Academic use
- Core SAS
- SAS ViyaFree
- Full platform
- Cloud-native
- AI/ML
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
Which should you pick?
Choose SAS if
- You need statistical analysis.
- You want to start without paying.
- You work on Linux, Windows, Web.
- You also want machine learning.
Choose BigQuery ML if
- You need sql-based ml.
- You want to start without paying.
- You also want automl tables.
Questions people ask
- Is SAS or BigQuery ML better?
- Neither clearly leads. SAS starts at Free and BigQuery ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, SAS or BigQuery ML?
- SAS starts at Free and BigQuery ML at Free.
- Does SAS or BigQuery ML run on more platforms?
- SAS runs on Linux, Windows, Web. BigQuery ML runs on Web.
- Can I use SAS for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is SAS best used for?
- SAS is most often used for regulated statistical analysis and clinical reporting, enterprise data management, visualization and decisioning on one licensed platform. Of those, regulated statistical analysis and clinical reporting and enterprise data management, visualization and decisioning on one licensed platform are not what BigQuery ML is typically brought in for.
- What can SAS do that BigQuery ML cannot?
- SAS covers Statistical analysis, Machine learning, Forecasting, Text analytics. BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Both handle Web support.
Related pages
More on BigQuery ML
Keep looking
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