Amazon Deequ

6.4easy start · #13 of 26
in Database Testing Tools

Free to practise onnot on record
Free trialnot on record
Well documentedyes
Runs where you workyes

Runs on api, Linux, Mac, self-hosted, Windows.

Amazon Deequ is ranked #13 of 26 in database testing tools on The Geeks Club. It runs on API, Linux, macOS, Self-hosted, Windows. There is a free plan.

Amazon Deequ plans and pricing

All plans

Apache 2.0 open-source library Free Requires Apache Spark; release must match Spark version github.com · 5 Oct 2026

Compared on database testing tools

Schema migration tests: Yes
Data quality checks: Yes
Test execution: self_hosted
Test language: Scala, Java, DQDL, SQL

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The record

Purpose: Deequ is an Apache Spark library for defining data unit tests that measure quality in large datasets.
Data scale: The project says Deequ is designed for very large datasets, including billions of rows, typically stored in a distributed filesystem or data warehouse.
Checks: Checks can validate row counts, completeness, uniqueness, allowed values, nonnegative values, patterns, and approximate quantiles.
Profiling and monitoring: Examples cover data profiling, persisting and querying computed metrics, anomaly detection over time, automatic constraint suggestions, and incremental metrics computation.
DQDL: Deequ supports the declarative Data Quality Definition Language, including rules for counts, completeness, uniqueness, statistics, schema matching, freshness, and custom SQL.
Row-level results: Row-level evaluation identifies rows that pass or fail supported rules, while dataset-level rules such as RowCount and Mean are marked as skipped.
Compatibility: Deequ releases target specific Apache Spark versions; versions 2.1.0 and later require Java 11, and the README lists Spark 3.1 through 3.5 compatibility for Deequ 2.x.
Installation: The README provides Maven and sbt dependency examples and directs users to select a release matching their Spark version.
Python interface: The project points Python users to PyDeequ, described on its repository as a Python API for Deequ.
AWS relationship: AWS Glue Data Quality documentation says that managed service is built on the open-source Deequ framework and uses DQDL.
License: The library is licensed under Apache 2.0.
Security reporting: The repository security policy asks users not to report security concerns in public GitHub issues and directs them to AWS's Vulnerability Disclosure Program or email.
Contribution and feedback: The README welcomes feedback and contributions.
Scale: The project says it is designed for very large datasets, including billions of rows, typically stored in distributed filesystems or data warehouses.
Price from: Free

Where it ranks on The Geeks Club

Best Database Testing Tools in 2026#13 of 26
Best Secrets Scanning Software in 2026#14 of 23

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Sources

github.com/awslabs/deequ· checked 4 Oct 2026
github.com/awslabs/python-deequ· checked 4 Oct 2026
docs.aws.amazon.com/en_en/glue/latest/dg/glue-data-quality.· checked 4 Oct 2026
github.com/awslabs/deequ/security/policy· checked 4 Oct 2026
github.com/awslabs/deequ/blob/master/CONTRIBUTING.· checked 5 Oct 2026