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Machine Learning · head to head

BigQuery ML vs KNIME

BigQuery ML logo

BigQuery ML

Machine Learning

Machine learning in BigQuery using SQL

From
Free
Rated
-
KNIME logo

KNIME

Machine Learning

Open source data analytics and integration platform

From
Free
Rated
-

The short version

  • Each has a real cost: BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it; KNIME the free Analytics Platform runs locally only, so anything shared or scheduled requires a paid Hub
  • They diverge on capability: BigQuery ML covers SQL-based ML, KNIME covers Visual workflows.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where BigQuery ML and KNIME differ
AttributeBigQuery MLKNIME
Pricing modelusage-basedfreemium
PlatformsWebLinux, Mac, Windows
Founded20082004

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning).

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
  • Cloud Storage

Only in KNIME

  • Visual workflows
  • Data preprocessing
  • Machine learning
  • Visualization
  • Reporting
  • Python
  • R
  • Spark

Both cover

  • TensorFlow

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 KNIME
  • Linear and logistic regression on warehouse datanot KNIME
  • K-means clustering and matrix factorisation for recommendationsnot KNIME
  • Time series forecasting with ARIMA_PLUSnot KNIME
  • Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot KNIME

KNIME

  • Data science and machine learning workflowsnot BigQuery ML
  • ETL and data pipeline automationnot BigQuery ML
  • Predictive analytics and modelingnot 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

KNIME

  • The free Analytics Platform runs locally only, so anything shared or scheduled requires a paid Hub
  • The free AI assistant is limited to 20 interactions a month
  • Paid workflow runtime is metered in credits, with 120 included on Pro and overage at $0.025 per vCore minute
  • The Team plan at $99 a month includes 3 members, with additional seats at $49 a month each
  • Business Hub pricing is on request, and its tiers are capped at 4, 8 and 16 vCores with 5, 5 and 20 users

Pricing, plan by plan

BigQuery ML

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

KNIME

Free
  • Analytics PlatformFree
    • 300+ data sources
    • Unlimited local processing
    • K-AI assistant (20 interactions/month)
  • Pro$19/month
    • 120 workflow runtime credits
    • Data app deployment
    • K-AI (500 interactions/month)
  • Team$99/month
    • All Pro features
    • Collaboration spaces for up to 3 team members
    • Additional members: $49/month each
  • Business Hub$null/month
    • Enterprise automation and governance
    • LDAP/OAuth authentication
    • Staged deployment

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 KNIME if

  • You need visual workflows.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want data preprocessing.

Questions people ask

Is BigQuery ML or KNIME better?
Neither clearly leads. BigQuery ML starts at Free and KNIME at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery ML or KNIME?
BigQuery ML starts at Free and KNIME at Free.
Does BigQuery ML or KNIME run on more platforms?
BigQuery ML runs on Web. KNIME runs on Linux, Mac, Windows.
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 KNIME is typically brought in for.
What can BigQuery ML do that KNIME cannot?
BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. KNIME covers Visual workflows, Data preprocessing, Machine learning, Visualization. Both handle TensorFlow.

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
KNIME: Is KNIME free?

Yes, KNIME Analytics Platform is free with 300+ data sources, unlimited local processing, and 20 K-AI assistant interactions per month.

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
KNIME: What do KNIME paid plans cost?

Pro plan starts at $19/month with 120 runtime credits. Team plan starts at $99/month for up to 3 members, with additional members at $49/month each.

Source
KNIME: What is KNIME's runtime credit system?

Pro and Team plans include runtime credits for workflow execution. Additional runtime beyond included credits costs $0.025 per vCore minute.

Source
KNIME: Does KNIME offer enterprise pricing?

Yes, Business Hub is available for enterprises needing automation, governance, LDAP/OAuth auth, and dedicated resources. Pricing available on request.

Source
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