Software · head to head
BigQuery ML vs Weka
The short version
- Each has a real cost: BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it; Weka the package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
- They diverge on capability: BigQuery ML covers SQL-based ML, Weka covers Classification.
Where they differ
Only the attributes on which BigQuery ML and Weka actually diverge.
| Attribute | BigQuery ML | Weka |
|---|---|---|
| Pricing model | usage-based | open-source |
| Platforms | Web | Linux, Mac, Windows |
| Founded | 2008 | 1993 |
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 BigQuery ML
- SQL-based ML
- AutoML Tables
- Model export
- Prediction functions
- Feature preprocessing
- BigQuery
- Vertex AI
- TensorFlow
Only in Weka
- Classification
- Regression
- Clustering
- Association rules
- Feature selection
- Java
- R
- Python
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 Weka
- Linear and logistic regression on warehouse datanot Weka
- K-means clustering and matrix factorisation for recommendationsnot Weka
- Time series forecasting with ARIMA_PLUSnot Weka
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Weka
Weka
- Teaching and exploring classic machine learning algorithms through a GUInot BigQuery ML
- Running data mining experiments and preprocessing without writing codenot 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
Weka
- The package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
- Weka is split into a stable 3.8 branch that receives only bug fixes and compatibility-safe upgrades and a 3.9 development branch that may receive features that break compatibility
- Weka requires a 64-bit Java VM; the bundled installers ship Bellsoft OpenJDK 25 per platform and architecture
Pricing, plan by plan
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
Weka
Free- Open SourceFree
- All ML algorithms
- GUI and CLI
- Java API
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 Weka if
- You need classification.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want regression.
Questions people ask
- Is BigQuery ML or Weka better?
- Neither clearly leads. BigQuery ML starts at Free and Weka at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, BigQuery ML or Weka?
- BigQuery ML starts at Free and Weka at Free.
- Does BigQuery ML or Weka run on more platforms?
- BigQuery ML runs on Web. Weka runs on Linux, Mac, Windows.
- 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 Weka is typically brought in for.
- What can BigQuery ML do that Weka cannot?
- BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Weka covers Classification, Regression, Clustering, Association rules.
Related pages
More on BigQuery ML
Keep looking
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