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Machine Learning & Data Science · head to head

BigQuery ML vs OpenAI API

BigQuery ML logo

BigQuery ML

Machine Learning & Data Science

Machine learning in BigQuery using SQL

From
Free
Rated
-
Full reviewWebsite
OpenAI API logo

OpenAI API

Machine Learning & Data Science

GPT and DALL-E APIs for developers

From
$0.15/per-million-tokens
Rated
-
Full reviewWebsite

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; OpenAI API new accounts start with a $100 approved monthly usage limit and must spend cumulatively to graduate tiers
  • They diverge on capability: BigQuery ML covers SQL-based ML, OpenAI API covers GPT models.

Where they differ

Only the attributes on which BigQuery ML and OpenAI API actually diverge.

Attributes where BigQuery ML and OpenAI API differ
AttributeBigQuery MLOpenAI API
Starting priceFree$0.15/per-million-tokens
Free tierYesNo
PlatformsWebApi
Founded20082015

Identical on both: pricing model (usage-based), user rating (Not yet rated), category (Machine Learning & Data Science).

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 OpenAI API

  • GPT models
  • DALL-E
  • Whisper
  • Embeddings
  • REST API
  • SDKs
  • Azure OpenAI
  • Api 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 OpenAI API
  • Linear and logistic regression on warehouse datanot OpenAI API
  • K-means clustering and matrix factorisation for recommendationsnot OpenAI API
  • Time series forecasting with ARIMA_PLUSnot OpenAI API
  • Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot OpenAI API

OpenAI API

  • Calling hosted language models from an applicationnot BigQuery ML
  • Generating images, audio and embeddings through one APInot BigQuery ML
  • Building agents and tool calling workflows on managed modelsnot 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

OpenAI API

  • New accounts start with a $100 approved monthly usage limit and must spend cumulatively to graduate tiers
  • Reaching the top Tier 5 monthly cap of $200,000 requires $1,000 of cumulative paid usage
  • Rate limits apply simultaneously across requests per minute, requests per day, tokens per minute, tokens per day and images per minute, and the first one hit blocks the request
  • API access is restricted to approved geographies

Pricing, plan by plan

BigQuery ML

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

OpenAI API

$0.15/per-million-tokens
  • GPT-4o mini$0.15/per-million-input-tokens
    • Fast
    • Affordable
  • GPT-4o$5/per-million-input-tokens
    • Multimodal
    • 128K context

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 OpenAI API if

  • You need gpt models.
  • You work on Api.
  • You also want dall-e.
OpenAI API review

Questions people ask

Is BigQuery ML or OpenAI API better?
Neither clearly leads. BigQuery ML starts at Free and OpenAI API at $0.15/per-million-tokens, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery ML or OpenAI API?
BigQuery ML has a free tier; the other does not. Paid plans start at Free for BigQuery ML and $0.15/per-million-tokens for OpenAI API.
Does BigQuery ML or OpenAI API run on more platforms?
BigQuery ML runs on Web. OpenAI API runs on Api.
Can I use BigQuery ML for free?
Yes. BigQuery ML has a free tier, so you can try it without paying. OpenAI API starts at $0.15/per-million-tokens.
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 OpenAI API is typically brought in for.
What can BigQuery ML do that OpenAI API cannot?
BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. OpenAI API covers GPT models, DALL-E, Whisper, Embeddings.
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