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Machine Learning · head to head

BigQuery ML vs Lightdash

BigQuery ML logo

BigQuery ML

Machine Learning

Machine learning in BigQuery using SQL

From
Free
Rated
-
Full reviewWebsite
Lightdash logo

Lightdash

Business Intelligence

Open-source BI for dbt users

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; Lightdash requires existing dbt infrastructure, not suitable for teams without data models
  • They diverge on capability: BigQuery ML covers SQL-based ML, Lightdash covers dbt Integration.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where BigQuery ML and Lightdash differ
AttributeBigQuery MLLightdash
Pricing modelusage-basedUnknown
PlatformsWebWeb, Cloud (managed), Self-hosted (on-premise)
CategoryMachine LearningBusiness Intelligence
Founded20082021

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 Lightdash

  • dbt Integration
  • Metrics Layer
  • Dashboards
  • Scheduling
  • Version Control
  • dbt
  • Snowflake
  • 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 Lightdash
  • Linear and logistic regression on warehouse datanot Lightdash
  • K-means clustering and matrix factorisation for recommendationsnot Lightdash
  • Time series forecasting with ARIMA_PLUSnot Lightdash
  • Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Lightdash

Lightdash

  • 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

Lightdash

  • Requires existing dbt infrastructure, not suitable for teams without data models
  • Enterprise features and AI agents unavailable in open-source MIT-licensed core

Pricing, plan by plan

BigQuery ML

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

Lightdash

Free
  • Open SourceFree
    • MIT-licensed core
    • Self-hostable
    • dbt integration
  • Cloud Managed$undefined/mo
    • Managed hosting
    • Premium features
    • AI agent capabilities

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 Lightdash if

  • You need dbt integration.
  • You want to start without paying.
  • You work on Web, Cloud (managed), Self-hosted (on-premise).
  • You also want metrics layer.
Lightdash review

Questions people ask

Is BigQuery ML or Lightdash better?
Neither clearly leads. BigQuery ML starts at Free and Lightdash at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery ML or Lightdash?
BigQuery ML starts at Free and Lightdash at Free.
Does BigQuery ML or Lightdash run on more platforms?
BigQuery ML runs on Web. Lightdash runs on Web, Cloud (managed), Self-hosted (on-premise).
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 Lightdash is typically brought in for.
What can BigQuery ML do that Lightdash cannot?
BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Lightdash covers dbt Integration, Metrics Layer, Dashboards, Scheduling. 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
Lightdash: Is Lightdash free?

Yes. Lightdash is free and open source under the MIT license. Self-hosting is completely free. Managed cloud services and enterprise features require separate licensing.

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
Lightdash: How does Lightdash integrate with dbt?

Lightdash reads dbt models and metric definitions directly. A team defines metrics once in dbt and reuses them across dashboards, exploration, and AI agents without redefinition.

Source
Lightdash: Does Lightdash support SQL queries?

Yes. As a modern BI platform for analysts, Lightdash supports full SQL capabilities alongside dbt model exploration and visual query builders.

Source
Lightdash: What are Lightdash AI agents?

Lightdash AI agents, available on paid plans, allow natural language queries against your data, generating SQL and visualizations automatically from questions.

Source
Lightdash: Can Lightdash be self-hosted?

Yes. Lightdash's MIT-licensed core is completely self-hostable and free. Enterprise features and AI agents ship under separate licensing.

Source
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