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Machine Learning · head to head

BigQuery ML vs C3 AI Suite

BigQuery ML logo

BigQuery ML

Machine Learning

Machine learning in BigQuery using SQL

From
Free
Rated
-
Full reviewWebsite
C3 AI Suite logo

C3 AI Suite

AI

Model-driven application platform for building enterprise AI on top of existing operational systems

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; C3 AI Suite the commercial model bundles software with heavy professional services, so the licence line in the quote understates the first-year cost by a wide margin and budgets set from the licence alone overrun.
  • They diverge on capability: BigQuery ML covers SQL-based ML, C3 AI Suite covers Type system.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which BigQuery ML and C3 AI Suite actually diverge.

Attributes where BigQuery ML and C3 AI Suite differ
AttributeBigQuery MLC3 AI Suite
Starting priceFreeOn request
Pricing modelusage-basedquote
Free tierYesNo
PlatformsWebWeb, Linux
CategoryMachine LearningAI
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 C3 AI Suite

  • Type system
  • Pre-built applications
  • Model lifecycle
  • C3 Generative AI
  • Multi-cloud deployment
  • FedRAMP and IL environments

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 C3 AI Suite
  • Linear and logistic regression on warehouse datanot C3 AI Suite
  • K-means clustering and matrix factorisation for recommendationsnot C3 AI Suite
  • Time series forecasting with ARIMA_PLUSnot C3 AI Suite
  • Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot C3 AI Suite

C3 AI Suite

  • A utility with decades of SCADA history wanting failure prediction on transformers without hiring a data science teamnot BigQuery ML
  • A defence agency needing an AI platform accredited for classified environments rather than a commercial SaaSnot BigQuery ML
  • An oil and gas operator consolidating condition data from OSIsoft PI, SAP and bespoke historians into one modelnot BigQuery ML
  • A bank building transaction monitoring where the vendor supplies both the models and the analysts who tune themnot 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

C3 AI Suite

  • The commercial model bundles software with heavy professional services, so the licence line in the quote understates the first-year cost by a wide margin and budgets set from the licence alone overrun.
  • Applications are written against C3 proprietary types, so nothing built on the platform ports to a generic Spark or Databricks stack without a rewrite, which makes exit expensive after two or three years.
  • Contracts have historically been large multi-year commitments with a small number of very large customers, which means pricing is negotiated case by case and small buyers get little leverage.
  • Skills are scarce outside C3 itself, so hiring an engineer who already knows the platform is hard and the customer stays dependent on the vendor for extensions.
  • Pre-built applications need substantial configuration against the customer data model before they produce anything, so the marketing claim of a packaged app understates the integration work by months.

Pricing, plan by plan

BigQuery ML

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

C3 AI Suite

On request
  • C3 AI Suite$undefined/year
    • Platform subscription sized by application and data volume
    • Paid pilot engagement typically precedes a subscription
    • Professional services quoted separately

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 C3 AI Suite if

  • You need type system.
  • You work on Web, Linux.
  • You also want pre-built applications.
C3 AI Suite review

Questions people ask

Is BigQuery ML or C3 AI Suite better?
Neither clearly leads. BigQuery ML starts at Free and C3 AI Suite at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery ML or C3 AI Suite?
BigQuery ML has a free tier; the other does not. Paid plans start at Free for BigQuery ML and On request for C3 AI Suite.
Does BigQuery ML or C3 AI Suite run on more platforms?
BigQuery ML runs on Web. C3 AI Suite 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. C3 AI Suite 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 C3 AI Suite is typically brought in for.
What can BigQuery ML do that C3 AI Suite cannot?
BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. C3 AI Suite covers Type system, Pre-built applications, Model lifecycle, C3 Generative AI.

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
C3 AI Suite: Does C3 publish pricing?

No. Everything is quoted, and the shape of the deal, pilot then subscription, means the first number you see is for a proof of value rather than the platform.

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
C3 AI Suite: Can it run in a classified environment?

Yes. C3 supports air-gapped and government cloud deployments, including FedRAMP-authorised environments, which is a large part of why defence buyers choose it.

C3 AI Suite: Do we own the models we build?

You own the models and the data. The application logic is written in C3 types, so the artefacts are portable in principle and impractical to move in practice.

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