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Head-to-head · ETL Testing Tools

dbt Cloud vs Great Expectations

  • Updated Nov 2026
  • Both researched from official sources
  • 5 checks side by side
Higher score dbt Cloud #6 in ETL Testing Tools 8.0/10 Free tier · Starter from $100/mo Free plan✓ 2 of 4 features Visit dbt Cloud
Great Expectations #7 in ETL Testing Tools 7.8/10 Free plan Free plan✓ 2 of 4 features Visit Great Expectations

dbt Cloud leads on 0 checks, Great Expectations on 0, and 5 are even. Who comes out ahead on the 5 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoredbt Cloud · 8.0/10
  • Free planboth

dbt Cloud scores higher on our rubric for etl testing tools: 8.0 against 7.8 out of 10; our editors rank them #6 and #7.

On deployment model, Great Expectations gives you Self-hosted where dbt Cloud offers Cloud.

dbt Cloud is the better fit for SQL-first teams already transforming data in the warehouse with dbt. Great Expectations is the better fit for engineering teams that want validation defined and versioned as code, for free.

  • dbt Cloud fits best

    SQL-first teams already transforming data in the warehouse with dbt

  • Great Expectations fits best

    Engineering teams that want validation defined and versioned as code, for free

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Side by side

Feature dbt Cloud 8.0/10 Visit ↗ Great Expectations 7.8/10 Visit ↗
At a glance
Editor score 8.0 7.8
Ranking #6 in ETL Testing Tools #7 in ETL Testing Tools
Best for SQL-first teams already transforming data in the warehouse with dbt Engineering teams that want validation defined and versioned as code, for free
Pricing model Free plan + paid Free plan + paid
Starting price $100/mo Free plan
Free plan ✓ ✓
Free trial — —
Features dbt Cloud 2/4 · Great Expectations 2/4
Source-to-target reconciliation — —
No-code test authoring — —
CI/CD integration ✓ ✓
API access ✓ ✓
Specs
Deployment model Cloud Self-hosted
Our review
Pros
  • Tests are version-controlled alongside the models they check, in the same project and pull request
  • Free tier is enough to try real tests on a real project before paying anything
  • Huge community package ecosystem (dbt packages) adds ready-made test macros for common checks
  • No licensing cost for the open-source core, and it's widely used so answers are easy to find
  • Its validation assertions read as plain English and double as documentation of what the data should look like
  • Integrates into most Python-based pipelines (Airflow, dbt, pandas, Spark) without a proprietary agent
Cons
  • It tests transformations you write in dbt, not a true black-box source-to-target reconciliation across arbitrary systems
  • Row-level and cross-database comparison testing needs extra packages or a companion tool
  • Starter plan pricing is per-seat, which adds up for larger analytics teams
  • No GUI for non-engineers; writing and maintaining expectations assumes comfort with Python
  • Self-hosting means your own team owns scaling, uptime, and upgrades
  • GX Cloud (the hosted option) is a separate product with its own evaluation, not just "the paid tier"
Our verdict

dbt Cloud isn't an ETL testing tool in the "point it at two systems and diff them" sense the rest of this list is — it's a transformation platform where tests are a first-class part of the workflow, declared right next to the SQL model…

Read the review →

Great Expectations is the tool we'd point a Python-comfortable data engineering team to when the budget line for ETL testing is zero but the standards still need to be real. "Expectations" are declared as code, which means they're…

Read the review →
  1. dbt CloudETL Testing Tools 8.0Free tier · Starter from $100/mo
  2. Great ExpectationsETL Testing Tools 7.8Free plan

Strengths and trade-offs

  • dbt Cloud — where it wins

    • Tests are version-controlled alongside the models they check, in the same project and pull request
    • Free tier is enough to try real tests on a real project before paying anything
    • Huge community package ecosystem (dbt packages) adds ready-made test macros for common checks

    Where it doesn't

    • It tests transformations you write in dbt, not a true black-box source-to-target reconciliation across arbitrary systems
    • Row-level and cross-database comparison testing needs extra packages or a companion tool
    • Starter plan pricing is per-seat, which adds up for larger analytics teams
  • Great Expectations — where it wins

    • No licensing cost for the open-source core, and it's widely used so answers are easy to find
    • Its validation assertions read as plain English and double as documentation of what the data should look like
    • Integrates into most Python-based pipelines (Airflow, dbt, pandas, Spark) without a proprietary agent

    Where it doesn't

    • No GUI for non-engineers; writing and maintaining expectations assumes comfort with Python
    • Self-hosting means your own team owns scaling, uptime, and upgrades
    • GX Cloud (the hosted option) is a separate product with its own evaluation, not just "the paid tier"

More comparisons

Reviewed by iTechGuides Editors · Editorial team · Updated Nov 2026

Last updated · How we research and update