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Machine Learning · head to head

BigQuery ML vs Feedzai

BigQuery ML logo

BigQuery ML

Machine Learning

Machine learning in BigQuery using SQL

From
Free
Rated
-
Full reviewWebsite
Feedzai logo

Feedzai

Cybersecurity

Real-time transaction fraud and financial crime detection for banks and payment processors

From
On request
Rated
-
Full reviewWebsite

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; Feedzai pricing is per transaction with an annual minimum, so a bank with seasonal or growing volume commits to a floor it may not use and pays overage above the band.
  • They diverge on capability: BigQuery ML covers SQL-based ML, Feedzai covers Real-time scoring.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

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

Attributes where BigQuery ML and Feedzai differ
AttributeBigQuery MLFeedzai
Starting priceFreeOn request
Pricing modelusage-basedquote
Free tierYesNo
PlatformsWebWeb, Linux
CategoryMachine LearningCybersecurity
Founded2008Unknown

Identical on both: user rating (Not yet rated).

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 Feedzai

  • Real-time scoring
  • Rule and model hybrid
  • Case manager
  • Behavioural biometrics
  • Model explainability
  • Deployment options

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

Feedzai

  • A bank joining an instant payments scheme where transfers are irrevocable and post-hoc recovery is impossiblenot BigQuery ML
  • A card issuer whose existing rules engine cannot be changed without a release, so fraud waves run for daysnot BigQuery ML
  • An acquirer needing per-merchant risk models rather than one portfolio-wide modelnot BigQuery ML
  • A bank required by its regulator to explain automated declines to customers, which rules out opaque scoringnot 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

Feedzai

  • Pricing is per transaction with an annual minimum, so a bank with seasonal or growing volume commits to a floor it may not use and pays overage above the band.
  • It sits in the authorisation path, which makes every upgrade a change-controlled event with rollback plans, and the operational burden falls on the bank rather than the vendor.
  • Out of the box models need months of the customer own labelled fraud history before they beat the rules they replace, so the value case starts late.
  • AML and fraud are licensed as separate modules, so institutions expecting one platform fee find the transaction monitoring capability is a second line item.
  • The buyer profile is large institutions, so smaller banks and fintechs face minimums that make per-transaction economics unattractive below significant scale.

Pricing, plan by plan

BigQuery ML

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

Feedzai

On request
  • Feedzai Financial Crime Platform$undefined/year
    • Priced by transaction volume with annual minimum commitment
    • Modules for fraud, AML and account opening licensed separately
    • Cloud, private cloud and on-premises deployment

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 Feedzai if

  • You need real-time scoring.
  • You work on Web, Linux.
  • You also want rule and model hybrid.
Feedzai review

Questions people ask

Is BigQuery ML or Feedzai better?
Neither clearly leads. BigQuery ML starts at Free and Feedzai at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery ML or Feedzai?
BigQuery ML has a free tier; the other does not. Paid plans start at Free for BigQuery ML and On request for Feedzai.
Does BigQuery ML or Feedzai run on more platforms?
BigQuery ML runs on Web. Feedzai runs on Web, Linux.
Can I use BigQuery ML for free?
Yes. BigQuery ML has a free tier, so you can try it without paying. Feedzai starts at On request.
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 Feedzai is typically brought in for.
What can BigQuery ML do that Feedzai cannot?
BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Feedzai covers Real-time scoring, Rule and model hybrid, Case manager, Behavioural biometrics.

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.

Source
Feedzai: Can Feedzai run on-premises?

Yes. On-premises and private cloud deployments are supported, which is why it appears in markets where transaction data cannot legally leave the country.

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.

Source
Feedzai: Does it cover AML as well as fraud?

It does, but transaction monitoring is a separately licensed module. Assume two line items if you want both.

Feedzai: How fast are decisions?

Designed for the authorisation window, typically tens of milliseconds. This is the constraint that rules out batch scoring architectures.

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