Software · head to head
BigQuery ML vs DataRobot

DataRobot
Software
Enterprise AI platform for automated machine learning
- From
- On request
- Rated
- -
The short version
- Only BigQuery ML has a free tier, so it costs nothing to try first.
- Each has a real cost: BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it; DataRobot model transparency is limited, often resembling a black box with limited explainability
- They diverge on capability: BigQuery ML covers SQL-based ML, DataRobot covers Automated ML.
Where they differ
Only the attributes on which BigQuery ML and DataRobot actually diverge.
| Attribute | BigQuery ML | DataRobot |
|---|---|---|
| Starting price | Free | On request |
| Pricing model | usage-based | subscription |
| Free tier | Yes | No |
| Founded | 2008 | 2012 |
Identical on both: platforms (Web), 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 DataRobot
- Automated ML
- Model deployment
- Time series
- MLOps
- Model monitoring
- Snowflake
- Databricks
- AWS
Both cover
- 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 DataRobot
- Linear and logistic regression on warehouse datanot DataRobot
- K-means clustering and matrix factorisation for recommendationsnot DataRobot
- Time series forecasting with ARIMA_PLUSnot DataRobot
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot DataRobot
DataRobot
- 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
DataRobot
- Model transparency is limited, often resembling a black box with limited explainability
- Requires integration with separate data manipulation tools for complex data transformation
- Lacks native Python and R code customization for proprietary algorithms
- Dependence on cloud connectivity means offline capabilities are not available
- Uploading sensitive data to third-party servers raises data privacy and security concerns
Pricing, plan by plan
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
DataRobot
On request- TrialFree
- Limited access
- Basic features
- EnterpriseFree
- Full platform
- AutoML
- MLOps
Which should you pick?
Choose BigQuery ML if
- You need sql-based ml.
- You want to start without paying.
- You also want automl tables.
Questions people ask
- Is BigQuery ML or DataRobot better?
- Neither clearly leads. BigQuery ML starts at Free and DataRobot at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, BigQuery ML or DataRobot?
- BigQuery ML has a free tier; the other does not. Paid plans start at Free for BigQuery ML and On request for DataRobot.
- Does BigQuery ML or DataRobot run on more platforms?
- Both run on Web, so platform support will not decide this one for you.
- Can I use BigQuery ML for free?
- Yes. BigQuery ML has a free tier, so you can try it without paying. DataRobot starts at On request.
- 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 DataRobot is typically brought in for.
- What can BigQuery ML do that DataRobot cannot?
- BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. DataRobot covers Automated ML, Model deployment, Time series, MLOps. Both handle Web support.
Answered from the vendors’ own pages
DataRobot: Does DataRobot require data science expertise?
DataRobot automates much of the ML pipeline including data preparation, feature engineering, and model selection, making it more accessible to non-experts, though it is still an enterprise platform.
SourceDataRobot: What does DataRobot cost?
DataRobot uses custom enterprise pricing with typical starting costs around $2,500 per month for smaller organizations. For 10 users, monthly costs range from $15,000 to $20,000. Implementation and professional services are 20-40% of first-year contract value.
SourceDataRobot: Does DataRobot support generative AI?
Yes, DataRobot offers generative AI capabilities with API-first integrations for LLMs, vector databases, and embedding models.
SourceDataRobot: Can DataRobot handle unstructured data?
Yes, DataRobot supports machine learning on both structured and unstructured data, including deep learning, NLP, and image analysis.
SourceRelated pages
More on BigQuery ML
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