Software · head to head
Stata vs BigQuery ML
The short version
- Only BigQuery ML has a free tier, so it costs nothing to try first.
- Each has a real cost: Stata the entry Stata/BE edition is capped at 2,048 variables and 798 independent variables in a model; BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it
- They diverge on capability: Stata covers Statistical analysis, BigQuery ML covers SQL-based ML.
Where they differ
Only the attributes on which Stata and BigQuery ML actually diverge.
| Attribute | Stata | BigQuery ML |
|---|---|---|
| Starting price | $48/year | Free |
| Pricing model | subscription | usage-based |
| Free tier | No | Yes |
| Platforms | Linux, Mac, Windows | Web |
| Founded | 1985 | 2008 |
Identical on both: 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 Stata
- Statistical analysis
- Data management
- Graphics
- Econometrics
- Survey analysis
- Python
- ODBC
- Excel
Only in BigQuery ML
- SQL-based ML
- AutoML Tables
- Model export
- Prediction functions
- Feature preprocessing
- BigQuery
- Vertex AI
- TensorFlow
What people use each for
The jobs each tool is most often brought in to do.
Stata
- Statistical analysis and econometrics on panel and survey datanot BigQuery ML
- Reproducible research with do files and logsnot BigQuery ML
- Teaching quantitative methods to studentsnot BigQuery ML
BigQuery ML
- Training models in SQL without exporting datanot Stata
- Linear and logistic regression on warehouse datanot Stata
- K-means clustering and matrix factorisation for recommendationsnot Stata
- Time series forecasting with ARIMA_PLUSnot Stata
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Stata
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Stata
- The entry Stata/BE edition is capped at 2,048 variables and 798 independent variables in a model
- Raising the variable limit to 32,767 requires Stata/SE and 120,000 requires Stata/MP
- Stata/MP is licensed by core count, so 2 core and 4 core licences are priced separately
- Student licences require proof of enrolment at a degree granting institution
- Stata/MP is not sold on a 6 month student term
- Perpetual student licences cost several times the annual price, for example $298 against $94 for Stata/BE
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
Stata
$48/year- Stata/BE$48/year
- Basic edition
- Core features
- Stata/SE$295/year
- Standard edition
- Larger datasets
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 Stata if
- You need statistical analysis.
- You work on Linux, Mac, Windows.
- You also want data management.
Choose BigQuery ML if
- You need sql-based ml.
- You want to start without paying.
- You also want automl tables.
Questions people ask
- Is Stata or BigQuery ML better?
- Neither clearly leads. Stata starts at $48/year and BigQuery ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Stata or BigQuery ML?
- BigQuery ML has a free tier; the other does not. Paid plans start at $48/year for Stata and Free for BigQuery ML.
- Does Stata or BigQuery ML run on more platforms?
- Stata runs on Linux, Mac, Windows. BigQuery ML runs on Web.
- Can I use BigQuery ML for free?
- Yes. BigQuery ML has a free tier, so you can try it without paying. Stata starts at $48/year.
- What is Stata best used for?
- Stata is most often used for statistical analysis and econometrics on panel and survey data, reproducible research with do files and logs, teaching quantitative methods to students. Of those, statistical analysis and econometrics on panel and survey data and reproducible research with do files and logs are not what BigQuery ML is typically brought in for.
- What can Stata do that BigQuery ML cannot?
- Stata covers Statistical analysis, Data management, Graphics, Econometrics. BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions.