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Machine Learning · head to head

BigQuery ML vs Redash

BigQuery ML logo

BigQuery ML

Machine Learning

Machine learning in BigQuery using SQL

From
Free
Rated
-
Full reviewWebsite
Redash logo

Redash

Spreadsheets

Connect and visualize your data

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; Redash pricing model not disclosed on dedicated pricing page
  • They diverge on capability: BigQuery ML covers SQL-based ML, Redash covers SQL Query Editor.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where BigQuery ML and Redash differ
AttributeBigQuery MLRedash
Pricing modelusage-basedfreemium
PlatformsWebWeb, Self-hosted, Cloud
CategoryMachine LearningSpreadsheets
Founded20082013

Identical on both: starting price (Free), free tier (Yes), 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 Redash

  • SQL Query Editor
  • Multiple Data Sources
  • Visualizations
  • Dashboards
  • Alerts
  • 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 Redash
  • Linear and logistic regression on warehouse datanot Redash
  • K-means clustering and matrix factorisation for recommendationsnot Redash
  • Time series forecasting with ARIMA_PLUSnot Redash
  • Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Redash

Redash

  • Data visualization and business intelligence for analyticsnot BigQuery ML
  • Query result sharing and collaborative dashboard creationnot 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

Redash

  • Pricing model not disclosed on dedicated pricing page
  • Open-source offering may require self-hosting technical expertise
  • Managed hosting or commercial support pricing not published

Pricing, plan by plan

BigQuery ML

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

Redash

Free
  • Open SourceFree
    • Full Features
    • Self-hosted
    • Community Support
  • Cloud$49/month
    • Managed Hosting
    • Automatic Updates
    • Support

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 Redash if

  • You need sql query editor.
  • You want to start without paying.
  • You work on Web, Self-hosted, Cloud.
  • You also want multiple data sources.
Redash review

Questions people ask

Is BigQuery ML or Redash better?
Neither clearly leads. BigQuery ML starts at Free and Redash at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery ML or Redash?
BigQuery ML starts at Free and Redash at Free.
Does BigQuery ML or Redash run on more platforms?
BigQuery ML runs on Web. Redash runs on Web, Self-hosted, Cloud.
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 Redash is typically brought in for.
What can BigQuery ML do that Redash cannot?
BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Redash covers SQL Query Editor, Multiple Data Sources, Visualizations, Dashboards. 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
Redash: What is Redash's pricing?

Redash is a popular open-source project with no pricing tiers listed on the pricing page. The project emphasizes no vendor lock-in and community contribution. Paid managed hosting or commercial support options may be available but are not published on this page.

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
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