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Machine Learning · head to head

BigQuery ML vs Chartio

BigQuery ML logo

BigQuery ML

Machine Learning

Machine learning in BigQuery using SQL

From
Free
Rated
-
Full reviewWebsite
Chartio logo

Chartio

Business Intelligence

Cloud-based data exploration (discontinued)

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; Chartio product was discontinued and sunset on March 1, 2022 after company acquisition by Atlassian
  • They diverge on capability: BigQuery ML covers SQL-based ML, Chartio covers Visual Query Builder.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where BigQuery ML and Chartio differ
AttributeBigQuery MLChartio
Starting priceFreeOn request
Pricing modelusage-basedUnknown
Free tierYesNo
CategoryMachine LearningBusiness Intelligence
Founded20082010

Identical on both: platforms (Web), 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
  • Vertex AI
  • TensorFlow
  • Cloud Storage

Only in Chartio

  • Visual Query Builder
  • Interactive Dashboards
  • Data Blending
  • Collaboration
  • Embedding
  • PostgreSQL
  • MySQL
  • Redshift

Both cover

  • BigQuery
  • Web support

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

Chartio

  • Drag and drop chart building over SQL databasesnot BigQuery ML
  • Shared business dashboards for non-technical teamsnot BigQuery ML
  • Exploring warehouse data without writing SQLnot 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

Chartio

  • Product was discontinued and sunset on March 1, 2022 after company acquisition by Atlassian
  • No current pricing available as service no longer operates
  • Users were migrated to alternative Atlassian solutions

Pricing, plan by plan

BigQuery ML

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

Chartio

On request
  • DiscontinuedFree
    • Service ended March 2022

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 Chartio if

  • You need visual query builder.
  • You also want interactive dashboards.
Chartio review

Questions people ask

Is BigQuery ML or Chartio better?
Neither clearly leads. BigQuery ML starts at Free and Chartio at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery ML or Chartio?
BigQuery ML has a free tier; the other does not. Paid plans start at Free for BigQuery ML and On request for Chartio.
Does BigQuery ML or Chartio run on more platforms?
Both run on Web, so platform support will not decide this one for you.
Can I use BigQuery ML for free?
Yes. BigQuery ML has a free tier, so you can try it without paying. Chartio 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 Chartio is typically brought in for.
What can BigQuery ML do that Chartio cannot?
BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Chartio covers Visual Query Builder, Interactive Dashboards, Data Blending, Collaboration. Both handle BigQuery, Web support.

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
Chartio: Is Chartio still available?

No, Chartio was discontinued on March 1, 2022. The product was acquired by Atlassian and the service was shut down. Users were offered migration to alternative solutions.

Source
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
Chartio: What should I use instead of Chartio after its discontinuation?

Atlassian, which acquired Chartio, recommends users migrate to other data visualization and business intelligence tools within the Atlassian ecosystem or compatible alternatives.

Source
Chartio: Can I still access Chartio's pricing information?

No, historical pricing is not relevant as Chartio ceased operations in March 2022. Any archived pricing information would not reflect current market options.

Source
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