Machine Learning · head to head
BigQuery ML vs Fathom
BigQuery ML
Machine Learning
Machine learning in BigQuery using SQL
- From
- Free
- Free plan
- Yes
The short version
- Each has a real cost: BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it; Fathom team plan requires minimum 2 users; cannot purchase single seat at team pricing
- They diverge on capability: BigQuery ML covers SQL-based ML, Fathom covers Auto-recording.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which BigQuery ML and Fathom actually diverge.
| Attribute | BigQuery ML | Fathom |
|---|---|---|
| Pricing model | usage-based | Unknown |
| Platforms | Web | Web, Zoom, Google Meet, Microsoft Teams |
| Category | Machine Learning | AI |
| Founded | 2008 | 2020 |
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
- BigQuery
- Vertex AI
- TensorFlow
Only in Fathom
- Auto-recording
- AI summaries
- Transcription
- Highlight clips
- Zoom
- Google Meet
- HubSpot
- Salesforce
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 Fathom
- Linear and logistic regression on warehouse datanot Fathom
- K-means clustering and matrix factorisation for recommendationsnot Fathom
- Time series forecasting with ARIMA_PLUSnot Fathom
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Fathom
Fathom
- AI-powered meeting transcription and automatic note-taking for sales teams and professionalsnot BigQuery ML
- Meeting analysis with AI scorecards and action item generation that syncs to CRMsnot 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
Fathom
- Team plan requires minimum 2 users; cannot purchase single seat at team pricing
- CRM field sync and deal view summaries available only on Business plan ($34/user/month) and above
Pricing, plan by plan
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
Fathom
FreeNo published plan breakdown. See the Fathom review.
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 Fathom if
- You need auto-recording.
- You want to start without paying.
- You work on Web, Zoom, Google Meet, Microsoft Teams.
- You also want ai summaries.
Questions people ask
- Is BigQuery ML or Fathom better?
- Neither clearly leads. BigQuery ML starts at Free and Fathom at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, BigQuery ML or Fathom?
- BigQuery ML starts at Free and Fathom at Free.
- Does BigQuery ML or Fathom run on more platforms?
- BigQuery ML runs on Web. Fathom runs on Web, Zoom, Google Meet, Microsoft Teams.
- 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 Fathom is typically brought in for.
- What can BigQuery ML do that Fathom cannot?
- BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Fathom covers Auto-recording, AI summaries, Transcription, Highlight clips. 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.
SourceFathom: What is the most affordable paid plan for individuals, and what does it include?
Fathom Premium costs $20 per month (or $16 per month billed annually). It includes advanced summaries, action items, and a conversational AI assistant, in addition to the features in the free plan.
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.
SourceFathom: What is included in Fathom's free plan?
The free plan includes unlimited recordings, transcriptions, AI summaries, clips, and playlists at no cost forever.
SourceFathom: How much does the Team plan cost per user, and what features does it add?
The Team plan costs $19 per month per user (minimum 2 users, or $15 per month annually). It includes everything from Premium plus global search, collaboration features, and team playlists.
SourceFathom: What trial or guarantee is available before committing to a paid plan?
All paid plans offer a 90-day guarantee to test features risk-free.
SourceFathom: Does Fathom offer free or discounted plans for startups or nonprofits?
Yes, qualified portfolio companies get up to 2 years free, and nonprofits can apply for 10 free seats.
SourceRelated pages
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- Fathom vs AWS SageMaker
- Fathom vs Azure Machine Learning
- Fathom vs DataRobot
- Fathom vs Databricks
- Fathom vs SAS
- Fathom vs scikit-learn
- Fathom vs Snowflake
- Fathom vs Weka
- Fathom vs MATLAB
- Fathom vs Palantir Foundry
- Fathom vs Apache Spark MLlib
- Fathom vs ClearML
- Fathom vs Cohere
- Fathom vs Dask
- Fathom vs Groq
- Fathom vs Haystack
- Fathom vs IBM SPSS
- Fathom vs Amazon Redshift ML
- Fathom vs Stable Diffusion
- Fathom vs Together AI
- Fathom vs AI21 Labs
- Fathom vs Banana
- Fathom vs DeepSeek
- Fathom vs Grok
- Fathom vs NotebookLM
- Fathom vs RunPod
- Fathom vs Pika
- Fathom vs D-ID
- Fathom vs Anthropic API
- Fathom vs ChatGPT
- Fathom vs Rev
- Fathom vs Aider
- Fathom vs Lambda Labs
- Fathom vs Leonardo AI
- Fathom vs Murf