Software · head to head
BigQuery ML vs Weights & Biases
The short version
- Each has a real cost: BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it; Weights & Biases pricing can be prohibitive for large teams without enterprise discounts
- They diverge on capability: BigQuery ML covers SQL-based ML, Weights & Biases covers Experiment tracking.
Where they differ
Only the attributes on which BigQuery ML and Weights & Biases actually diverge.
| Attribute | BigQuery ML | Weights & Biases |
|---|---|---|
| Pricing model | usage-based | Unknown |
| Platforms | Web | Web, Python SDK, REST API |
| Founded | 2008 | 2017 |
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
- Cloud Storage
Only in Weights & Biases
- Experiment tracking
- Dataset versioning
- Model registry
- Hyperparameter sweeps
- Collaborative dashboards
- PyTorch
- Keras
- Hugging Face
Both cover
- TensorFlow
- 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 Weights & Biases
- Linear and logistic regression on warehouse datanot Weights & Biases
- K-means clustering and matrix factorisation for recommendationsnot Weights & Biases
- Time series forecasting with ARIMA_PLUSnot Weights & Biases
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Weights & Biases
Weights & Biases
- 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
Weights & Biases
- Pricing can be prohibitive for large teams without enterprise discounts
- Limited integrations compared to some competitors
- Dashboard customization options limited on lower plans
- Requires some setup and configuration knowledge
Pricing, plan by plan
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
Weights & Biases
Free- FreeFree
- 5 model seats
- 5 GB storage
- 1 GB/month Weave ingestion
- Pro$60/month
- 10 seats
- 100 GB storage
- Private projects
- Teams$179/month
- Team collaboration
- Advanced analytics
- Dedicated support
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 Weights & Biases if
- You need experiment tracking.
- You want to start without paying.
- You work on Web, Python SDK, REST API.
- You also want dataset versioning.
Questions people ask
- Is BigQuery ML or Weights & Biases better?
- Neither clearly leads. BigQuery ML starts at Free and Weights & Biases at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, BigQuery ML or Weights & Biases?
- BigQuery ML starts at Free and Weights & Biases at Free.
- Does BigQuery ML or Weights & Biases run on more platforms?
- BigQuery ML runs on Web. Weights & Biases runs on Web, Python SDK, REST API.
- 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 Weights & Biases is typically brought in for.
- What can BigQuery ML do that Weights & Biases cannot?
- BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Weights & Biases covers Experiment tracking, Dataset versioning, Model registry, Hyperparameter sweeps. Both handle TensorFlow, Web support.
Answered from the vendors’ own pages
Weights & Biases: Does Weights & Biases have a free plan?
Yes. The Free tier includes 5 model seats, 5 GB storage, and 1 GB/month Weave ingestion. Academic users get unlimited tracked hours, 200 GB storage, and 100 seats at no cost.
SourceWeights & Biases: What are the paid plans for Weights & Biases?
Pro starts at $60/month with 10 seats and 100 GB storage. Team plans start at $179/month. Enterprise pricing is custom.
SourceWeights & Biases: What machine learning features does W&B provide?
Weights & Biases captures hyperparameters, metrics, and model outputs automatically. Features include experiment tracking, interactive Reports for sharing findings, Artifacts for managing datasets and models, advanced hyperparameter sweeps, and model deployment tools.
SourceRelated pages
More on BigQuery ML
More on Weights & Biases
Keep looking
Other head to heads
- BigQuery ML vs AWS SageMaker
- BigQuery ML vs Google Vertex AI
- BigQuery ML vs Azure Machine Learning
- BigQuery ML vs DataRobot
- BigQuery ML vs Snowflake
- BigQuery ML vs TensorFlow
- BigQuery ML vs Comet ML
- BigQuery ML vs Keras
- BigQuery ML vs MLflow
- BigQuery ML vs Jupyter
- BigQuery ML vs PyTorch
- BigQuery ML vs scikit-learn
- BigQuery ML vs Apache Spark MLlib
- BigQuery ML vs Alteryx
- BigQuery ML vs Anaconda
- BigQuery ML vs Databricks
- BigQuery ML vs Dataiku
- BigQuery ML vs DVC
- Weights & Biases vs AWS SageMaker
- Weights & Biases vs Google Vertex AI
- Weights & Biases vs Azure Machine Learning
- Weights & Biases vs DataRobot
- Weights & Biases vs Snowflake
- Weights & Biases vs TensorFlow
- Weights & Biases vs Comet ML
- Weights & Biases vs Keras
- Weights & Biases vs MLflow
- Weights & Biases vs Jupyter
- Weights & Biases vs PyTorch
- Weights & Biases vs scikit-learn
- Weights & Biases vs Apache Spark MLlib
- Weights & Biases vs Alteryx
- Weights & Biases vs Anaconda
- Weights & Biases vs Databricks
- Weights & Biases vs Dataiku
- Weights & Biases vs DVC