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Machine Learning · head to head

BigQuery ML vs GoodData

BigQuery ML logo

BigQuery ML

Machine Learning

Machine learning in BigQuery using SQL

From
Free
Rated
-
GoodData logo

GoodData

Business Intelligence

Analytics platform for data products

From
On request
Rated
-

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; GoodData pricing scales per workspace as customer base grows, increasing costs with scale
  • They diverge on capability: BigQuery ML covers SQL-based ML, GoodData covers Headless BI.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where BigQuery ML and GoodData differ
AttributeBigQuery MLGoodData
Starting priceFreeOn request
Pricing modelusage-basedUnknown
Free tierYesNo
PlatformsWebWeb, Cloud AWS, Cloud Azure
CategoryMachine LearningBusiness Intelligence
Founded20082007

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
  • Vertex AI
  • TensorFlow
  • Cloud Storage

Only in GoodData

  • Headless BI
  • Semantic Layer
  • Embedded Analytics
  • Multi-tenancy
  • White-labeling
  • Snowflake
  • Redshift
  • PostgreSQL

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

GoodData

  • Self-service analyticsnot BigQuery ML
  • Data explorationnot BigQuery ML
  • Ad-hoc reportingnot BigQuery ML
  • Collaborative analysisnot BigQuery ML
  • Embedded analyticsnot 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

GoodData

  • Pricing scales per workspace as customer base grows, increasing costs with scale
  • Advanced security features like audit logging and HIPAA compliance only on Enterprise plan

Pricing, plan by plan

BigQuery ML

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

GoodData

On request
  • Professional$undefined/mo
    • Core BI and analytics
    • Full embedding with whitelabeling
    • Multi-tenancy support
  • Enterprise$undefined/mo
    • All Professional features
    • Custom agents and Agent Builder
    • 99.5% guaranteed uptime SLA

Which should you pick?

Choose BigQuery ML if

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

Choose GoodData if

  • You need headless bi.
  • You work on Web, Cloud AWS, Cloud Azure.
  • You also want semantic layer.

Questions people ask

Is BigQuery ML or GoodData better?
Neither clearly leads. BigQuery ML starts at Free and GoodData at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery ML or GoodData?
BigQuery ML has a free tier; the other does not. Paid plans start at Free for BigQuery ML and On request for GoodData.
Does BigQuery ML or GoodData run on more platforms?
BigQuery ML runs on Web. GoodData runs on Web, Cloud AWS, Cloud Azure.
Can I use BigQuery ML for free?
Yes. BigQuery ML has a free tier, so you can try it without paying. GoodData 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 GoodData is typically brought in for.
What can BigQuery ML do that GoodData cannot?
BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. GoodData covers Headless BI, Semantic Layer, Embedded Analytics, Multi-tenancy. 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
GoodData: Does GoodData offer a free tier?

No, GoodData does not offer a free tier. The platform has Professional and Enterprise pricing tiers that require sales contact for quotes.

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
GoodData: What data warehouses can GoodData connect to?

GoodData supports direct connections to Snowflake, BigQuery, Redshift, Azure Databricks, and PostgreSQL through a direct-query-only integration model.

Source
GoodData: Can you self-host GoodData?

Self-hosted deployment is only available on the Enterprise plan. Professional plan customers are limited to the managed SaaS offering.

Source
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