Deequ is an open-source library, built on Apache Spark, for defining unit tests for data and measuring data quality in large datasets. Users declare checks such as completeness, uniqueness, value sets and quantile thresholds; Deequ computes metrics with Spark jobs and evaluates the assertions against them. It also supports data profiling, constraint suggestion, incremental metrics, metric persistence and anomaly detection on quality metrics over time. The library is written in Scala, with Java examples, and is added to a Spark project as a Maven or sbt dependency; a separate project, PyDeequ, offers a Python interface.
Deequ is published under the Apache License 2.0 in the awslabs GitHub organisation, which is run by Amazon Web Services, a US company. It is a library rather than a hosted service: it runs inside the Spark environment you operate, so where data is processed depends on that environment. Because the code is open, a European organisation can inspect it, fork it and run it on infrastructure in its own jurisdiction.