Machine Learning · head to head
BigQuery ML vs Equals
Equals
Spreadsheets
A real spreadsheet with SQL result sets landing in its cells, now sold only on annual contracts starting at 24,000 USD
- From
- $24000/year
- 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; Equals the price list now starts at 24,000 USD a year with no monthly billing and no self-serve signup, having offered a free plan in 2023 and 39 USD per seat in 2024, so any team that evaluated it previously is looking at a different product commercially.
- They diverge on capability: BigQuery ML covers SQL-based ML, Equals covers Connected sheets.
- Prices and features above were last checked on 31 August 2026.
Where they differ
Only the attributes on which BigQuery ML and Equals actually diverge.
| Attribute | BigQuery ML | Equals |
|---|---|---|
| Starting price | Free | $24000/year |
| Pricing model | usage-based | Per year by connector count and refresh frequency |
| Free tier | Yes | No |
| Platforms | Web | Web, API |
| Category | Machine Learning | Spreadsheets |
| Founded | 2008 | Unknown |
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 Equals
- Connected sheets
- Real spreadsheet mechanics
- Cell references into SQL
- Equals Warehouse
- Views
- Writeback
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 Equals
- Linear and logistic regression on warehouse datanot Equals
- K-means clustering and matrix factorisation for recommendationsnot Equals
- Time series forecasting with ARIMA_PLUSnot Equals
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Equals
Equals
- A revenue operations team that wants software metrics computed in a spreadsheet rather than defined in a BI semantic layernot BigQuery ML
- Analysts who need a SQL result and manual assumptions in the same file, with the assumptions visible as cellsnot BigQuery ML
- Joining Stripe, Salesforce and a production database without building a warehouse and pipeline firstnot BigQuery ML
- Distributing a recurring numbers pack to Slack, email or a wall display without rebuilding it as a dashboardnot 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
Equals
- The price list now starts at 24,000 USD a year with no monthly billing and no self-serve signup, having offered a free plan in 2023 and 39 USD per seat in 2024, so any team that evaluated it previously is looking at a different product commercially.
- Your data is copied out of your infrastructure by design, into a Snowflake warehouse that Equals operates, with Fivetran holding non-SQL source data in transit, and no self-hosted or bring-your-own-warehouse option is documented.
- The financial function category contains only IRR, NPV and PMT, with no XIRR, XNPV, FV, PV, RATE or NPER, and there is no LAMBDA, LET, OFFSET or INDIRECT, so a substantial class of existing spreadsheet models cannot be ported without rework.
- No documentation of importing or exporting Excel files exists anywhere in the docs index; the supported file sources are CSV and Google Sheets and the only documented export is dashboards as PDF, which is a notable gap for a product positioning itself as a successor to Excel.
- Data freshness is a pricing lever rather than a setting, at six hours on Essential, one hour on Business and fifteen minutes on Enterprise, and the feature that removes row limits is itself gated above the entry tier, so the Essential row ceiling is neither published nor unlimited.
Pricing, plan by plan
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
Equals
$24000/year- Essential$24000/year
- Unlimited viewers and unlimited editors
- 3 connectors
- Data sync every 6 hours
- Business$36000/year
- Unlimited viewers and unlimited editors
- 5 connectors or a warehouse connection
- Data sync every hour
- Enterprise$60000/year
- Unlimited viewers and unlimited editors
- Unlimited connectors or a warehouse connection
- Data sync every 15 minutes
- Connector add-ons$199/month
- 199 USD per month for each additional database or import script connector
- 699 USD per month for each additional connector of any other type
- Available on Business and Enterprise
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 Equals if
- You need connected sheets.
- You work on Web, API.
- You also want real spreadsheet mechanics.
Questions people ask
- Is BigQuery ML or Equals better?
- Neither clearly leads. BigQuery ML starts at Free and Equals at $24000/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, BigQuery ML or Equals?
- BigQuery ML has a free tier; the other does not. Paid plans start at Free for BigQuery ML and $24000/year for Equals.
- Does BigQuery ML or Equals run on more platforms?
- BigQuery ML runs on Web. Equals runs on Web, API.
- Can I use BigQuery ML for free?
- Yes. BigQuery ML has a free tier, so you can try it without paying. Equals starts at $24000/year.
- 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 Equals is typically brought in for.
- What can BigQuery ML do that Equals cannot?
- BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Equals covers Connected sheets, Real spreadsheet mechanics, Cell references into SQL, Equals Warehouse.
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.
SourceEquals: Is it a real spreadsheet or a modelling tool with a grid?
A real spreadsheet. A1 references, absolute reference locking, pivot tables and spilling array formulas all work, and SQL results land in ranges that ordinary cells reference.
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.
SourceEquals: What does it actually cost?
24,000 USD a year for Essential, 36,000 for Business and 60,000 for Enterprise, billed annually. There is no monthly option and no self-serve signup; the trial is negotiated per customer.
Equals: Are seats charged?
No. Viewers and editors are unlimited on every plan. The meters are connector count, refresh frequency and AI spend, with additional connectors at 199 or 699 USD a month.
Equals: Does my data stay in my own warehouse?
No. Connecting more than one source syncs data into a Snowflake warehouse that Equals runs, and non-SQL sources pass through Fivetran. There is no documented self-hosted option.
Related pages
More on BigQuery ML
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- Equals vs scikit-learn
- Equals vs Snowflake
- Equals vs Weka
- Equals vs MATLAB
- Equals vs Palantir Foundry
- Equals vs Apache Spark MLlib
- Equals vs Hugging Face
- Equals vs Kubeflow
- Equals vs Langwatch
- Equals vs LlamaIndex
- Equals vs Milvus
- Equals vs Neptune.ai
- Equals vs Amazon Redshift ML
- Equals vs Looker
- Equals vs Coefficient
- Equals vs Metabase
- Equals vs Redash
- Equals vs Quadratic
- Equals vs Sigma Computing
- Equals vs Tableau
- Equals vs Apache Superset
- Equals vs Teable
- Equals vs Baserow
- Equals vs Numbers
- Equals vs SeaTable
- Equals vs APITable
- Equals vs Cube Software
- Equals vs Mathesar
- Equals vs Rowy