Instead of Amazon Deequ
Amazon Deequ alternatives
Amazon Deequ gives Spark teams a free, Apache 2.0 library for defining data unit tests on very large datasets. Its checks cover counts, completeness, uniqueness, permitted values, patterns, and approximate quantiles; DQDL adds schema, freshness, statistics, and custom SQL rules. Profiling, saved metrics, anomaly detection, suggested constraints, incremental calculations, and row-level results extend those checks. Scala, Java, SQL, and PyDeequ provide ways to work with it, and releases target specific Spark versions.
- 1
DataKitchen TestGen
Free plan Open source APILinuxMac+3Automated database profiling and quality tests — TestGen profiles many database and file sources and generates tests, with predictive freshness, volume, schema, and custom-metric monitors.
- 2
Atlas
Free plan Open source APILinuxMac+3Versioned database schema changes — Atlas manages and migrates database schemas with declarative, versioned workflows rather than testing data quality.
- 3
Great Expectations
Free plan APILinuxMac+2Python data-validation workflows — Great Expectations offers a Python validation library, human-readable Data Docs, and integrations for data sources, notifications, and orchestration.
- 4
HammerDB
Free plan LinuxSelf-hostedWeb+1Database workload benchmarking — HammerDB runs database benchmarks and captures workload and performance metrics instead of validating data quality.
- 5
pgroll
Free plan Open source LinuxMacSelf-hosted+1Reversible PostgreSQL schema migrations — pgroll performs reversible PostgreSQL schema migrations while keeping old and new schema versions available, rather than checking data quality.
- 6
Soda
Free plan APILinuxSelf-hosted+1Data quality monitoring and contracts — Soda combines production observability, development-to-CI/CD testing, data contracts, and three deployment models.
- 7
Sqitch
Free plan LinuxMacSelf-hosted+1Framework-independent database change management — Sqitch manages database-native change scripts and their dependencies across many database engines, rather than validating datasets.
- 8
Avidemux
Free plan Open source LinuxMacWeb+1 - 9
Bytebase Enterprise
Free plan APISelf-hostedWeb - 10
Liquibase
Free plan APIExtensionLinux+3 - 11
DbFit
Free plan LinuxSelf-hostedWeb+1 - 12
Percona pstress
Free plan LinuxSelf-hosted - 13
SQLFluff
Free plan APILinuxMac+2 - 14
NBi
Free plan Windows - 15
SQLancer
Free plan LinuxMacWindows - 16
utPLSQL
Free plan LinuxMacSelf-hosted+1 - 17
Database Rider
Free plan Self-hosted - 18
pgtestdb
Free plan Self-hosted - 19
pgTAP
Free plan LinuxSelf-hosted - 20
ContextQA Database Testing
Free trial AndroidAPIiPhone+2 - 21
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tSQLt
Free plan Self-hosted - 23
QuerySurge
Free trial APILinuxSelf-hosted+2 - 24
Datafold
Paid APISelf-hostedWeb
The main constraint is the Spark requirement: teams must match Deequ releases to Spark, and version 2.1.0 onward requires Java 11. Execution is self-hosted, with no CI/CD or pull-request scanning. Alternatives may suit teams focused instead on automated database tests, validation workflows, schema changes, or performance benchmarking. Compare supported databases and languages, deployment choices, integrations, and whether you need data-quality monitoring or migration control. Also consider whether a free open-source tool or a paid plan fits your workflow.
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