Software · head to head
BigQuery ML vs Snowflake
The short version
- Each has a real cost: BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it; Snowflake no flat subscription price is published - cost varies by edition, cloud provider, and region and requires a separate calculator or credit-consumption table
- They diverge on capability: BigQuery ML covers SQL-based ML, Snowflake covers Separated Compute/Storage.
Where they differ
Only the attributes on which BigQuery ML and Snowflake actually diverge.
| Attribute | BigQuery ML | Snowflake |
|---|---|---|
| Pricing model | usage-based | Unknown |
| Platforms | Web | Web, API |
| Founded | 2008 | 2012 |
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 Snowflake
- Separated Compute/Storage
- Near-zero Maintenance
- Data Sharing
- Time Travel
- Cloning
- Multi-cluster Warehouse
- Semi-structured Data
- dbt
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 Snowflake
- Linear and logistic regression on warehouse datanot Snowflake
- K-means clustering and matrix factorisation for recommendationsnot Snowflake
- Time series forecasting with ARIMA_PLUSnot Snowflake
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Snowflake
Snowflake
- Cloud data warehousing and SQL analyticsnot BigQuery ML
- Data engineering and ELT pipelinesnot BigQuery ML
- Data sharing and marketplacenot BigQuery ML
- AI/ML workloads via Snowpark and Cortexnot BigQuery ML
- BI backend for tools such as Tableau and Power BInot 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
Snowflake
- No flat subscription price is published - cost varies by edition, cloud provider, and region and requires a separate calculator or credit-consumption table
- Free trial is capped at $400 in credits or 30 days, whichever comes first, not a perpetual free tier
- During the trial, certain features (external network access, hybrid tables, Openflow) are capped at 10 credits/day until a payment method is added
- Total cost combines compute credits, storage, and data transfer billed separately
Pricing, plan by plan
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
Snowflake
Free- Standard$undefined/mo
- Consumption-based, per-credit pricing
- Enterprise$undefined/mo
- Consumption-based, per-credit pricing
- Business Critical$undefined/mo
- Consumption-based, per-credit pricing
- Virtual Private Snowflake$undefined/mo
- Consumption-based, per-credit pricing
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 Snowflake if
- You need separated compute/storage.
- You want to start without paying.
- You work on Web, API.
- You also want near-zero maintenance.
Questions people ask
- Is BigQuery ML or Snowflake better?
- Neither clearly leads. BigQuery ML starts at Free and Snowflake at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, BigQuery ML or Snowflake?
- BigQuery ML starts at Free and Snowflake at Free.
- Does BigQuery ML or Snowflake run on more platforms?
- BigQuery ML runs on Web. Snowflake runs on Web, 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 Snowflake is typically brought in for.
- What can BigQuery ML do that Snowflake cannot?
- BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Snowflake covers Separated Compute/Storage, Near-zero Maintenance, Data Sharing, Time Travel. Both handle Web support.
Related pages
More on BigQuery ML
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