Tools

Data quality testing

6 tools compared: how each is priced, where it runs, and what to consider instead.

Tool	Pricing model	Free tier	Open source
cuallee Lightweight, DataFrame-agnostic Python library for writing data quality checks with one API across engines.	Open source + paid	Yes	Yes
Deequ Open-source Scala/Spark library from AWS for defining unit tests that measure data quality on large datasets.	Open source + paid	Yes	Yes
DQOps Data quality and observability platform with 150+ built-in checks, configurable via UI or YAML, with daily automated monitoring.	Subscription	No	No
Great Expectations Open-source Python framework for defining, running and documenting data quality tests ("expectations") in pipelines.	Free tier + paid	Yes	Yes
Pandera Open-source Python library that validates dataframes against a declared schema, catching bad data before it reaches a model or report.	Open source + paid	Yes	Yes
Soda Data quality testing platform combining a check-as-code language (SodaCL) with a SaaS UI for monitoring and collaboration.	Free tier + paid	Yes	No

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