Machine Learning & Data Science · head to head
Amazon Redshift ML vs BigQuery ML
Amazon Redshift ML
Machine Learning & Data Science
Create machine learning models using SQL
- From
- Free
- Rated
- -
BigQuery ML
Machine Learning & Data Science
Machine learning in BigQuery using SQL
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Amazon Redshift ML free tier covers only two CREATE MODEL requests per month for two months, capped at 100,000 cells per request; beyond that training is metered at $20 per million cells for the first 10 million, dropping in tiers to $7 per million cells over 100 million; BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it
- They diverge on capability: Amazon Redshift ML covers AutoML, BigQuery ML covers AutoML Tables.
Where they differ
Only the attributes on which Amazon Redshift ML and BigQuery ML actually diverge.
| Attribute | Amazon Redshift ML | BigQuery ML |
|---|---|---|
| Founded | 2006 | 2008 |
Identical on both: starting price (Free), pricing model (usage-based), free tier (Yes), platforms (Web), user rating (Not yet rated), category (Machine Learning & Data Science).
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 Amazon Redshift ML
- AutoML
- SageMaker integration
- BYOM support
- In-database predictions
- Amazon Redshift
- SageMaker
- S3
- Glue
Only in BigQuery ML
- AutoML Tables
- Model export
- Prediction functions
- Feature preprocessing
- BigQuery
- Vertex AI
- TensorFlow
- Cloud Storage
Both cover
- SQL-based ML
- Web support
What people use each for
The jobs each tool is most often brought in to do.
Amazon Redshift ML
- Training and running machine learning models directly from SQL inside Amazon Redshiftnot BigQuery ML
BigQuery ML
- Training models in SQL without exporting datanot Amazon Redshift ML
- Linear and logistic regression on warehouse datanot Amazon Redshift ML
- K-means clustering and matrix factorisation for recommendationsnot Amazon Redshift ML
- Time series forecasting with ARIMA_PLUSnot Amazon Redshift ML
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Amazon Redshift ML
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Amazon Redshift ML
- Free tier covers only two CREATE MODEL requests per month for two months, capped at 100,000 cells per request; beyond that training is metered at $20 per million cells for the first 10 million, dropping in tiers to $7 per million cells over 100 million
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
Amazon Redshift ML
Free- Free TrialFree
- 2-month trial
- 750 DC2.Large hours
- On-Demand$0.25/hour
- Per-node pricing
- SageMaker training
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 Amazon Redshift ML if
- You need automl.
- You want to start without paying.
- You also want sagemaker integration.
Choose BigQuery ML if
- You need automl tables.
- You want to start without paying.
- You also want model export.
Questions people ask
- Is Amazon Redshift ML or BigQuery ML better?
- Neither clearly leads. Amazon Redshift ML 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, Amazon Redshift ML or BigQuery ML?
- Amazon Redshift ML starts at Free and BigQuery ML at Free.
- Does Amazon Redshift ML or BigQuery ML run on more platforms?
- Both run on Web, so platform support will not decide this one for you.
- Can I use Amazon Redshift ML for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Amazon Redshift ML best used for?
- Amazon Redshift ML is most often used for training and running machine learning models directly from sql inside amazon redshift. Of those, training and running machine learning models directly from sql inside amazon redshift is not what BigQuery ML is typically brought in for.
- What can Amazon Redshift ML do that BigQuery ML cannot?
- Amazon Redshift ML covers AutoML, SageMaker integration, BYOM support, In-database predictions. BigQuery ML covers AutoML Tables, Model export, Prediction functions, Feature preprocessing. Both handle SQL-based ML, Web support.
Related pages
More on Amazon Redshift ML
More on BigQuery ML
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