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Head-to-head · ETL Testing Tools

RightData vs Apache Griffin

  • Updated Nov 2026
  • Both researched from official sources
  • 5 checks side by side
Higher score RightData #3 in ETL Testing Tools 8.7/10 Pricing on request ✓ 4 of 4 features Visit RightData
Apache Griffin #8 in ETL Testing Tools 7.3/10 Free (open source) Free plan✓ 1 of 4 features Visit Apache Griffin

RightData leads on 3 checks, Apache Griffin on 1, and 1 is 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 scoreRightData · 8.7/10
  • Free planonly Apache Griffin
  • Most featuresRightData · 4 of 4

RightData scores higher on our rubric for etl testing tools: 8.7 against 7.3 out of 10; our editors rank them #3 and #8.

Apache Griffin offers free plan; RightData doesn't. RightData offers no-code test authoring; Apache Griffin doesn't. RightData offers ci/cd integration; Apache Griffin doesn't. On deployment model, RightData gives you Hybrid where Apache Griffin offers Self-hosted. RightData offers api access; Apache Griffin doesn't.

RightData is the better fit for teams that want ETL validation, reconciliation, and governance tracked in one place. Apache Griffin is the better fit for big-data teams on Spark/Hadoop who want validation with zero license cost.

  • RightData fits best

    Teams that want ETL validation, reconciliation, and governance tracked in one place

  • Apache Griffin fits best

    Big-data teams on Spark/Hadoop who want validation with zero license cost

Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.

Side by side

Feature RightData 8.7/10 Visit ↗ Apache Griffin 7.3/10 Visit ↗
At a glance
Editor score 8.7 7.3
Ranking #3 in ETL Testing Tools #8 in ETL Testing Tools
Best for Teams that want ETL validation, reconciliation, and governance tracked in one place Big-data teams on Spark/Hadoop who want validation with zero license cost
Pricing model Paid Free
Starting price Pricing on request Free (open source)
Free plan — ✓ (best)
Free trial — —
Features RightData 4/4 · Apache Griffin 1/4
Source-to-target reconciliation ✓ ✓
No-code test authoring ✓ (best) —
CI/CD integration ✓ (best) —
API access ✓ (best) —
Specs
Deployment model Hybrid Self-hosted
Our review
Pros
  • Covers ETL validation and regression testing alongside migration validation in one product
  • Governance and cataloging features mean validation results connect to a broader data-trust story
  • Built for teams reconciling data across large migrations, not just routine nightly pipeline checks
  • No licensing cost at all, under the Apache Software Foundation
  • Built on Spark, so it scales the same way the big-data pipelines it checks already do
  • Supports both batch and streaming data quality measurement
Cons
  • No published pricing, so cost only becomes clear after a sales conversation
  • The governance/cataloging layer is more than a team that only wants ETL checks may need
  • Being positioned as a platform rather than a point tool means a longer evaluation before rollout
  • No vendor support line; help comes from community docs and mailing lists, not a support contract
  • Setup and ongoing maintenance assume real familiarity with Spark and the Hadoop ecosystem
  • Smaller, slower-moving community than more actively marketed commercial tools on this list
Our verdict

RightData reads less like a single-purpose ETL checker and more like a data quality platform that happens to do ETL validation very well. Reconciliation and regression testing sit next to cataloging and governance features, so the same…

Read the review →

Apache Griffin is the choice for a team that's already standardized on Spark for big-data processing and wants data quality and ETL validation to live in that same stack instead of adding a new vendor and a new connector to maintain. It…

Read the review →
  1. RightDataETL Testing Tools 8.7Pricing on request
  2. Apache GriffinETL Testing Tools 7.3Free (open source)

Strengths and trade-offs

  • RightData — where it wins

    • Covers ETL validation and regression testing alongside migration validation in one product
    • Governance and cataloging features mean validation results connect to a broader data-trust story
    • Built for teams reconciling data across large migrations, not just routine nightly pipeline checks

    Where it doesn't

    • No published pricing, so cost only becomes clear after a sales conversation
    • The governance/cataloging layer is more than a team that only wants ETL checks may need
    • Being positioned as a platform rather than a point tool means a longer evaluation before rollout

  • Apache Griffin — where it wins

    • No licensing cost at all, under the Apache Software Foundation
    • Built on Spark, so it scales the same way the big-data pipelines it checks already do
    • Supports both batch and streaming data quality measurement

    Where it doesn't

    • No vendor support line; help comes from community docs and mailing lists, not a support contract
    • Setup and ongoing maintenance assume real familiarity with Spark and the Hadoop ecosystem
    • Smaller, slower-moving community than more actively marketed commercial tools on this list
  • RightData8.7/10 · Pricing on request

    Positions ETL validation as one piece of a broader data quality and governance platform.

    Visit RightDataFull verdict →
  • Apache Griffin7.3/10 · Free (open source)

    A no-cost, self-hosted option for teams already running Spark who want data quality checks in the same stack.

    Visit Apache GriffinFull verdict →

More comparisons

All ETL testing tools comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Nov 2026

Last updated · How we research and update