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Machine Learning & Data Science · head to head

BigQuery ML vs IBM SPSS

BigQuery ML logo

BigQuery ML

Machine Learning & Data Science

Machine learning in BigQuery using SQL

From
Free
Rated
-
Full reviewWebsite
IBM SPSS logo

IBM SPSS

Machine Learning & Data Science

Statistical analysis software for data science

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it; IBM SPSS add-on packages are priced separately from the base subscription, and the promotional 45% discount on them excludes renewals
  • They diverge on capability: BigQuery ML covers SQL-based ML, IBM SPSS covers Statistical analysis.

Where they differ

Only the attributes on which BigQuery ML and IBM SPSS actually diverge.

Attributes where BigQuery ML and IBM SPSS differ
AttributeBigQuery MLIBM SPSS
Pricing modelusage-basedsubscription
PlatformsWebLinux, Mac, Windows
Founded20081911

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 BigQuery ML

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

Only in IBM SPSS

  • Statistical analysis
  • Predictive modeling
  • Data visualization
  • Survey analysis
  • Decision trees
  • Python
  • R
  • Excel

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 IBM SPSS
  • Linear and logistic regression on warehouse datanot IBM SPSS
  • K-means clustering and matrix factorisation for recommendationsnot IBM SPSS
  • Time series forecasting with ARIMA_PLUSnot IBM SPSS
  • Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot IBM SPSS

IBM SPSS

  • Statistical testing and regression analysis for academic and market researchnot BigQuery ML
  • Predictive modelling and forecasting without writing codenot 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

IBM SPSS

  • Add-on packages are priced separately from the base subscription, and the promotional 45% discount on them excludes renewals
  • Subscription cost renews at the then current price at the end of the first year, so the advertised rate applies to the first term only
  • Prices shown are described by IBM as indicative, vary by country and exclude applicable taxes and duties
  • Extended access periods of 12 months or more are handled as tailored pricing rather than a published rate
  • Advanced statistics, custom tables, decision trees and forecasting are separate add-ons rather than part of the base product

Pricing, plan by plan

BigQuery ML

Free
  • Free TierFree
    • 10GB storage
    • 1TB queries
  • On-Demand$5/TB
    • Pay per TB scanned
    • ML training costs

IBM SPSS

Free
  • TrialFree
    • 14-day trial
    • Full features
  • Base$99/month
    • Core statistics
    • Data management

Which should you pick?

Choose BigQuery ML if

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

Choose IBM SPSS if

  • You need statistical analysis.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want predictive modeling.
IBM SPSS review

Questions people ask

Is BigQuery ML or IBM SPSS better?
Neither clearly leads. BigQuery ML starts at Free and IBM SPSS at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery ML or IBM SPSS?
BigQuery ML starts at Free and IBM SPSS at Free.
Does BigQuery ML or IBM SPSS run on more platforms?
BigQuery ML runs on Web. IBM SPSS runs on Linux, Mac, Windows.
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 IBM SPSS is typically brought in for.
What can BigQuery ML do that IBM SPSS cannot?
BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. IBM SPSS covers Statistical analysis, Predictive modeling, Data visualization, Survey analysis.
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