Best 9 Data Quality Tools for MariaDB (2026)

    Discover the 9 best open-source and managed data quality tools for MariaDB: 8 that connect to MariaDB and run checks on its data, and 1 that works from its metadata without reading table data. 2 of them are open source.

    By Ari Bajo - Data Engineer turned Writer.

    Updated on November 5, 2026

    Tools list

    Collate

    Managed agentic data platform built on OpenMetadata, with AI agents, data quality tests, observability metrics, column-level lineage, and governance workflows.

    My Opinion

    Best for data teams that want OpenMetadata fully managed, with enterprise support, security features, and advanced governance workflows.

    OpenMetadata

    Open-source context platform that unifies metadata for humans and AI agents, with data discovery, data quality tests, column-level lineage, and governance.

    My Opinion

    Best for data teams that want one self-hosted, open-source platform for discovery, data quality, and governance with a wide range of integrations.

    Ataccama ONE

    Agentic data trust platform with data quality rules, observability, a data catalog, lineage, master data management, and a built-in AI agent.

    My Opinion

    Best for large organizations that want enterprise data quality, master data management, and data governance from one vendor.

    Acceldata

    Autonomous data and AI platform, born in data observability, with AI agents for data monitoring, lineage, governance, and cost optimization.

    My Opinion

    Best for large enterprises with hybrid or on-premise data estates that want observability, FinOps, and agentic data management from one vendor.

    Qualytics

    Data quality control layer that validates data where it's used, with checks auto-generated from profiling, anomaly detection, and quality context for AI agents.

    My Opinion

    Best for enterprises in regulated industries that need high test coverage without hand-writing rules, and on-premise deployment via Kubernetes.

    DQOps

    Open-source data quality operations center to profile, automate, and monitor data quality with built-in checks, monitors, and data quality KPI dashboards.

    My Opinion

    Best for data teams that want to customize built-in checks and track data quality KPIs on dashboards. The open-source version has had no releases since January 2026, so prefer DQOps Cloud.

    Datafold

    AI-powered data engineering platform with agents for migrations and code reviews, plus data diff, impact analysis, and anomaly detection.

    My Opinion

    Best for data teams planning a warehouse migration or wanting data diffs in every pull request to catch regressions before merge.

    SelectZero

    Self-hosted data observability platform with value-level data validation, column-level lineage, a data catalog, and a business glossary.

    My Opinion

    Best for enterprises that cannot let data leave their environment and want one self-hosted tool, deployed with Docker.

    Entropy Data

    Data product marketplace (formerly Data Mesh Manager) where every data product has an owner and data contracts based on the Open Data Contract Standard, from the team behind the open-source Data Contract CLI.

    My Opinion

    Best for organizations adopting data mesh that want a data product marketplace with ODCS data contracts, policy checks, and test results published from the Data Contract CLI.

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    By Ari Bajo - Data Engineer turned Writer.

    Frequently Asked Questions

    Which data quality tools run checks directly on MariaDB?
    8 of the 9 tools on this page connect to MariaDB and run checks, monitors, or profiling on the data itself: Collate, OpenMetadata, Ataccama ONE, Acceldata, Qualytics, DQOps, Datafold, and SelectZero. The others work from MariaDB metadata, runs, or lineage. Each card links to the tool's MariaDB integration docs. Read more on my data quality tool market guide.
    How can I edit this tools list?
    If you think a tool belongs here or you want to suggest an edit, I would love to hear from you. You can fill out the feedback form or DM on LinkedIn.