Softwr

Machine Learning & Data Science · head to head

Snowflake vs BigQuery ML

Snowflake logo

Snowflake

Machine Learning & Data Science

The AI Data Cloud for enterprise data warehousing

From
Free
Rated
-
Full reviewWebsite
BigQuery ML logo

BigQuery ML

Machine Learning & Data Science

Machine learning in BigQuery using SQL

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Snowflake no flat subscription price is published - cost varies by edition, cloud provider, and region and requires a separate calculator or credit-consumption table; BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it
  • They diverge on capability: Snowflake covers Separated Compute/Storage, BigQuery ML covers SQL-based ML.

Where they differ

Only the attributes on which Snowflake and BigQuery ML actually diverge.

Attributes where Snowflake and BigQuery ML differ
AttributeSnowflakeBigQuery ML
Pricing modelUnknownusage-based
PlatformsWeb, APIWeb
Founded20122008

Identical on both: starting price (Free), free tier (Yes), 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 Snowflake

  • Separated Compute/Storage
  • Near-zero Maintenance
  • Data Sharing
  • Time Travel
  • Cloning
  • Multi-cluster Warehouse
  • Semi-structured Data
  • dbt

Only in BigQuery ML

  • SQL-based ML
  • AutoML Tables
  • Model export
  • Prediction functions
  • Feature preprocessing
  • BigQuery
  • Vertex AI
  • TensorFlow

Both cover

  • Web support

What people use each for

The jobs each tool is most often brought in to do.

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

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

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

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

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

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

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 Snowflake if

  • You need separated compute/storage.
  • You want to start without paying.
  • You work on Web, API.
  • You also want near-zero maintenance.
Snowflake review

Choose BigQuery ML if

  • You need sql-based ml.
  • You want to start without paying.
  • You also want automl tables.
BigQuery ML review

Questions people ask

Is Snowflake or BigQuery ML better?
Neither clearly leads. Snowflake 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, Snowflake or BigQuery ML?
Snowflake starts at Free and BigQuery ML at Free.
Does Snowflake or BigQuery ML run on more platforms?
Snowflake runs on Web, API. BigQuery ML runs on Web.
Can I use Snowflake for free?
Both have a free tier, so you can try either at no cost before committing.
What is Snowflake best used for?
Snowflake is most often used for cloud data warehousing and sql analytics, data engineering and elt pipelines, data sharing and marketplace, ai/ml workloads via snowpark and cortex. Of those, cloud data warehousing and sql analytics and data engineering and elt pipelines are not what BigQuery ML is typically brought in for.
What can Snowflake do that BigQuery ML cannot?
Snowflake covers Separated Compute/Storage, Near-zero Maintenance, Data Sharing, Time Travel. BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Both handle Web support.
ShareXLinkedInRedditWhatsAppEmail

Related pages

More on Snowflake

More on BigQuery ML

Keep looking

Other head to heads