Software · head to head
Weka vs BigQuery ML
The short version
- Each has a real cost: Weka the package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution; BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it
- They diverge on capability: Weka covers Classification, BigQuery ML covers SQL-based ML.
Where they differ
Only the attributes on which Weka and BigQuery ML actually diverge.
| Attribute | Weka | BigQuery ML |
|---|---|---|
| Pricing model | open-source | usage-based |
| Platforms | Linux, Mac, Windows | Web |
| Founded | 1993 | 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 Weka
- Classification
- Regression
- Clustering
- Association rules
- Feature selection
- Java
- R
- Python
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.
Weka
- Teaching and exploring classic machine learning algorithms through a GUInot BigQuery ML
- Running data mining experiments and preprocessing without writing codenot BigQuery ML
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
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
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
Weka
Free- Open SourceFree
- All ML algorithms
- GUI and CLI
- Java API
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 Weka if
- You need classification.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want regression.
Choose BigQuery ML if
- You need sql-based ml.
- You want to start without paying.
- You also want automl tables.
Questions people ask
- Is Weka or BigQuery ML better?
- Neither clearly leads. Weka 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, Weka or BigQuery ML?
- Weka starts at Free and BigQuery ML at Free.
- Does Weka or BigQuery ML run on more platforms?
- Weka runs on Linux, Mac, Windows. BigQuery ML runs on Web.
- Can I use Weka for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Weka best used for?
- Weka is most often used for teaching and exploring classic machine learning algorithms through a gui, running data mining experiments and preprocessing without writing code. Of those, teaching and exploring classic machine learning algorithms through a gui and running data mining experiments and preprocessing without writing code are not what BigQuery ML is typically brought in for.
- What can Weka do that BigQuery ML cannot?
- Weka covers Classification, Regression, Clustering, Association rules. BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions.