Looking for the best data quality tools for Prefect? This list covers 3 tools that natively integrate with Prefect — from data testing and data observability to shift-left data quality and unified platforms.
Each tool below links directly to its Prefect integration documentation so you can evaluate support.
By Ari Bajo - Data Engineer turned Writer.
See the full data quality tools list
All 36 data quality, data testing, and data observability tools.
Open-source Python data quality framework, stewarded by Fivetran, with 50+ declarative expectations to validate files, SQL databases, warehouses, and DataFrames.
Best for Python data engineers who want a free, code-first testing library and don't need a managed UI, since GX Cloud is no longer available.
Data + AI observability platform that monitors data pipelines and AI agents in production, with column-level lineage and AI troubleshooting agents.
Best for large data teams ready to invest in a mature, widely adopted platform that monitors both their data and their AI agents.
Open-source dbt package by Boomi that adds anomaly detection tests and a CLI-generated data observability report to dbt projects.
Best for dbt teams that want free anomaly detection tests inside their existing dbt project, without a cloud account.
Data & AI control plane by Boomi with anomaly detection monitors, column-level lineage, incident management, a data catalog, and AI agents.
Best for dbt-centric analytics teams that want managed monitoring, lineage, and AI agents for triage on top of their dbt tests.
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By Ari Bajo - Data Engineer turned Writer.