Machine Learning · head to head
BigQuery ML vs Dundas BI

Dundas BI
Business Intelligence
Flexible business intelligence platform
- From
- $500/month
- 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; Dundas BI the published Embedded BI Package starts from about $4,738.70 USD per month billed annually for 8 core capacity
- They diverge on capability: BigQuery ML covers SQL-based ML, Dundas BI covers White-labeling.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which BigQuery ML and Dundas BI actually diverge.
| Attribute | BigQuery ML | Dundas BI |
|---|---|---|
| Starting price | Free | $500/month |
| Pricing model | usage-based | subscription |
| Free tier | Yes | No |
| Platforms | Web | Web, Embedded, Mobile |
| Category | Machine Learning | Business Intelligence |
| Founded | 2008 | 1992 |
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 Dundas BI
- White-labeling
- Embedded Analytics
- Data Preparation
- Custom Visualizations
- API
- SQL Server
- Oracle
- PostgreSQL
Both cover
- 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 Dundas BI
- Linear and logistic regression on warehouse datanot Dundas BI
- K-means clustering and matrix factorisation for recommendationsnot Dundas BI
- Time series forecasting with ARIMA_PLUSnot Dundas BI
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Dundas BI
Dundas BI
- Embedding dashboards and analytics inside another applicationnot BigQuery ML
- Self service business intelligence and ad hoc reportingnot BigQuery ML
- Building custom data visualisations against open BI APIsnot 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
Dundas BI
- The published Embedded BI Package starts from about $4,738.70 USD per month billed annually for 8 core capacity
- That figure reflects a limited time 35 percent promotional discount rather than list price
- Licensing is by CPU core capacity rather than by user, so cost scales with server hardware
- Dundas is now part of insightsoftware following acquisition
- The page states that a pricing plan is worked out together with the vendor rather than published as a rate card
Pricing, plan by plan
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
Dundas BI
$500/month- Professional$500/month
- Full Platform
- Embedding
- Support
- EnterpriseFree
- Unlimited Users
- Multi-tenant
- Premium 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.
Choose Dundas BI if
- You need white-labeling.
- You work on Web, Embedded, Mobile.
- You also want embedded analytics.
Questions people ask
- Is BigQuery ML or Dundas BI better?
- Neither clearly leads. BigQuery ML starts at Free and Dundas BI at $500/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, BigQuery ML or Dundas BI?
- BigQuery ML has a free tier; the other does not. Paid plans start at Free for BigQuery ML and $500/month for Dundas BI.
- Does BigQuery ML or Dundas BI run on more platforms?
- BigQuery ML runs on Web. Dundas BI runs on Web, Embedded, Mobile.
- Can I use BigQuery ML for free?
- Yes. BigQuery ML has a free tier, so you can try it without paying. Dundas BI starts at $500/month.
- 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 Dundas BI is typically brought in for.
- What can BigQuery ML do that Dundas BI cannot?
- BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Dundas BI covers White-labeling, Embedded Analytics, Data Preparation, Custom Visualizations. Both handle 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.
SourceDundas BI: How much does Dundas BI cost?
Dundas BI does not publish specific pricing. The vendor emphasizes 'smarter licensing models to scale appropriately and achieve ROI rapidly' and offers 'custom plans that fit your needs' rather than standardized tiers. Customers must contact Dundas directly for pricing quotes tailored to their enterprise or embedded analytics use case.
SourceBigQuery 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.
SourceDundas BI: What licensing options does Dundas BI offer?
Dundas BI describes their approach as flexible licensing designed to scale based on deployment needs. Specific licensing models and per-seat or concurrent-user costs are determined through custom quotes.
SourceRelated pages
More on BigQuery ML
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