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Head-to-head · ETL Testing Tools

Informatica Data Validation vs Apache Griffin

  • Updated Nov 2026
  • Both researched from official sources
  • 5 checks side by side
Higher score Informatica Data Validation #5 in ETL Testing Tools 8.2/10 Pricing on request ✓ 3 of 4 features Visit Informatica
Apache Griffin #8 in ETL Testing Tools 7.3/10 Free (open source) Free plan✓ 1 of 4 features Visit Apache Griffin

Informatica Data Validation leads on 2 checks, Apache Griffin on 1, and 2 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 scoreInformatica Data Validation · 8.2/10
  • Free planonly Apache Griffin
  • Most featuresInformatica Data Validation · 3 of 4

Informatica Data Validation scores higher on our rubric for etl testing tools: 8.2 against 7.3 out of 10; our editors rank them #5 and #8.

Apache Griffin offers free plan; Informatica Data Validation doesn't. Informatica Data Validation offers ci/cd integration; Apache Griffin doesn't. On deployment model, Informatica Data Validation gives you Hybrid where Apache Griffin offers Self-hosted. Informatica Data Validation offers api access; Apache Griffin doesn't.

Informatica Data Validation is the better fit for enterprises validating existing Informatica PowerCenter ETL workflows. Apache Griffin is the better fit for big-data teams on Spark/Hadoop who want validation with zero license cost.

  • Informatica Data Validation fits best

    Enterprises validating existing Informatica PowerCenter ETL workflows

  • 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 Informatica Data Validation 8.2/10 Visit ↗ Apache Griffin 7.3/10 Visit ↗
At a glance
Editor score 8.2 7.3
Ranking #5 in ETL Testing Tools #8 in ETL Testing Tools
Best for Enterprises validating existing Informatica PowerCenter ETL workflows 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 Informatica Data Validation 3/4 · Apache Griffin 1/4
Source-to-target reconciliation ✓ ✓
No-code test authoring — —
CI/CD integration ✓ (best) —
API access ✓ (best) —
Specs
Deployment model Hybrid Self-hosted
Our review
Pros
  • Deep, native fit with PowerCenter metadata and workflows rather than a bolt-on connector
  • Backed by Informatica's long enterprise support and services organization
  • Suited to regulated environments already standardized on the Informatica stack
  • 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
  • Pricing requires a sales conversation, typical for this tier but still opaque upfront
  • Real value is narrower outside a PowerCenter-centric estate than the other tools on this list
  • Implementations for a first rollout commonly run months, not days
  • 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

Informatica Data Validation makes the most sense as a "yes, and" purchase for a team that already runs PowerCenter: it reads the same metadata and workflows natively rather than treating Informatica as just another connector to configure,…

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. Informatica Data ValidationETL Testing Tools 8.2Pricing on request
  2. Apache GriffinETL Testing Tools 7.3Free (open source)

Strengths and trade-offs

  • Informatica Data Validation — where it wins

    • Deep, native fit with PowerCenter metadata and workflows rather than a bolt-on connector
    • Backed by Informatica's long enterprise support and services organization
    • Suited to regulated environments already standardized on the Informatica stack

    Where it doesn't

    • Pricing requires a sales conversation, typical for this tier but still opaque upfront
    • Real value is narrower outside a PowerCenter-centric estate than the other tools on this list
    • Implementations for a first rollout commonly run months, not days

  • 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
  • Informatica Data Validation8.2/10 · Pricing on request

    The default choice for shops already standardized on Informatica PowerCenter who need matching validation.

    Visit InformaticaFull 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