Machine Learning · head to head
BigQuery ML vs Minitab
Minitab
Machine Learning
Statistical software for quality engineering, and the tool Six Sigma training is written around
- From
- $2394/year
- 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; Minitab licensing is a per named user subscription, so an organisation where fifty engineers each need it twice a quarter pays fifty full seats for people who open it eight times a year.
- They diverge on capability: BigQuery ML covers SQL-based ML, Minitab covers Control charts.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which BigQuery ML and Minitab actually diverge.
| Attribute | BigQuery ML | Minitab |
|---|---|---|
| Starting price | Free | $2394/year |
| Pricing model | usage-based | subscription |
| Free tier | Yes | No |
| Platforms | Web | Mac, Windows, Web |
| Founded | 2008 | 1972 |
Identical on both: user rating (Not yet rated), category (Machine Learning).
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 Minitab
- Control charts
- Process capability analysis
- Measurement systems analysis
- Design of experiments
- Classical statistics
- Assistant
- Predictive Analytics module
- Desktop and browser access
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 Minitab
- Linear and logistic regression on warehouse datanot Minitab
- K-means clustering and matrix factorisation for recommendationsnot Minitab
- Time series forecasting with ARIMA_PLUSnot Minitab
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Minitab
Minitab
- Six Sigma and process improvement projects where the training materials and internal procedures already assume Minitabnot BigQuery ML
- Producing capability and gage studies as evidence for a customer audit or a regulatory submissionnot BigQuery ML
- Design of experiments on a production process, run by an engineer who will not be writing codenot BigQuery ML
- Quality departments that need credible statistics without hiring a statistician or a data scientistnot 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
Minitab
- Licensing is a per named user subscription, so an organisation where fifty engineers each need it twice a quarter pays fifty full seats for people who open it eight times a year.
- Analyses are recorded as a project file and a session log rather than as code, so reviewing what somebody did means reading output instead of reading a script, and reproducing it a year later depends on the same version still being installed.
- The machine learning capability is a separately licensed module with a fixed set of tree-based methods, so it is neither included in the base price nor competitive with what a Python user has for nothing.
- There is no deployment path in the statistical product, so putting a model into a running process means buying Minitab Model Ops as another product or reimplementing the model somewhere else entirely.
- Data handling is worksheet-shaped and held in memory, so anything past a few million rows means preparing the extract in another tool first, and joins and reshaping are clumsy compared with SQL or pandas.
Pricing, plan by plan
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
Minitab
$2394/year- Solution Center Core$2394/year
- Marked as Most Popular
- Best for quality professionals
- Minitab Dashboards
- Solution Center Analytics$2593.5/year
- Best for analytics professionals
- Includes predictive analytics capabilities
- Minitab Dashboards
- Solution Center Copilot$2793/year
- All-in-one platform for operational excellence
- Includes AI-powered insights
- Minitab Dashboards
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 Minitab if
- You need control charts.
- You work on Mac, Windows, Web.
- You also want process capability analysis.
Questions people ask
- Is BigQuery ML or Minitab better?
- Neither clearly leads. BigQuery ML starts at Free and Minitab at $2394/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, BigQuery ML or Minitab?
- BigQuery ML has a free tier; the other does not. Paid plans start at Free for BigQuery ML and $2394/year for Minitab.
- Does BigQuery ML or Minitab run on more platforms?
- BigQuery ML runs on Web. Minitab runs on Mac, Windows, Web.
- Can I use BigQuery ML for free?
- Yes. BigQuery ML has a free tier, so you can try it without paying. Minitab starts at $2394/year.
- 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 Minitab is typically brought in for.
- What can BigQuery ML do that Minitab cannot?
- BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Minitab covers Control charts, Process capability analysis, Measurement systems analysis, Design of experiments.
Answered from the vendors’ own pages
BigQuery ML: How much does Google Cloud BigQuery ML cost?
BigQuery ML pricing is not specified separately on Google Cloud's pricing page. It follows the same pay-as-you-go model as BigQuery, charging per terabyte of data scanned during analysis. Customers receive $300 in free credits and can use 20+ products free up to monthly limits.
SourceMinitab: Does Minitab run on macOS?
The installed desktop application is Windows. Mac users work through the browser version, which is included with the subscription but is not identical in every feature.
BigQuery ML: Does Google Cloud offer a free trial?
Yes, new customers get $300 in free credits and all customers can use 20+ Google Cloud products free up to their monthly usage limits.
SourceMinitab: Is it machine learning software?
Not primarily. It is a statistics package for quality and process work. Predictive modelling exists in a separate Predictive Analytics module and is limited to tree-based methods.
Minitab: Can I buy a perpetual licence?
The current offer is subscription based. Older perpetual licences exist in the field but are not the way the product is sold now.
Minitab: What is the difference between Minitab and Minitab Workspace or Engage?
Minitab Statistical Software does the analysis. Workspace and Engage are separate products for process mapping, project management and improvement programme governance, and are licensed separately.
Minitab: Can I automate it?
Only to a limited degree. There is a command language and integration options, but it is designed to be driven by a person through menus, not scheduled in a pipeline.
Related pages
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