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Apache Griffin review

Free#8 of 8 in ETL Testing Tools

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

7.3/10Editor score
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Apache Griffin7.3 Visit Apache Griffin

Reviewed by iTechGuides Editors · Editorial team · Updated Nov 2026

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 measures quality across both batch and streaming jobs, which fits teams whose pipelines aren't purely one or the other.

Being a fully open-source Apache project, there's no license fee and no sales process — but there's also no support line to call when something breaks. Troubleshooting runs through community documentation and mailing lists, which is a real tradeoff against the commercial tools on this list that bundle support into the price.

We'd recommend this specifically to teams with in-house Spark expertise who want validation under their own control. Teams without that expertise already in-house will likely spend more in engineering time than they'd save in license cost.

Apache Griffin pros and cons

  • 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

Apache Griffin fact sheet, pricing and score →

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