Discover the best 8 data quality tools that integrate with MariaDB.
By Ari Bajo - Data Engineer turned Writer.
See the full data quality tools list
All 36 data quality, data testing, and data observability tools.
Managed enterprise data platform built on OpenMetadata with data discovery, observability metrics, column-level lineage, governance workflows, and enterprise support.
Best for data teams looking for a fully managed enterprise version of OpenMetadata with dedicated support, advanced governance features, and a wide range of integrations.
Data trust platform with data quality evaluation rules, anomaly detection, data lineage, a data catalog, and master data management.
Best for organizations looking to scale data management initiatives with enterprise master data management, data quality, and data governance.
Agentic data observability platform with AI agents for data monitoring, data lineage, and FinOps.
Best for data teams looking for an enterprise data observability platform pivoting to a ChatGPT-like interface for all data management initiatives.
AI-powered data quality platform with auto-generated tests from profiling results, anomaly detection, and data quality context for humans and AI agents.
Best for enterprises in highly regulated industries looking for a scalable data quality platform with on-premise cloud deployments via Kubernetes.
Open-source data quality platform with 150+ Jinja2 SQL-based checks configurable via YAML or a local web UI, data lineage, and incident management. DQOps Cloud adds cloud storage for quality results, hosted Looker Studio dashboards, and team collaboration.
Best for data teams looking for a highly customizable open-source data quality check library with a local web UI and Looker Studio dashboard integrations. DQOps Cloud adds shared dashboards and multi-user collaboration without managing your own infrastructure.
Building or buying a data tool in 2026?
One email a month — a new market guide and tool list, straight to your inbox. Next up: Data Governance, LLMOps, Data Orchestration.
By Ari Bajo - Data Engineer turned Writer.
Proactive data quality platform with data diff tests, data impact reports, column-level lineage, and data monitors.
Best for data teams looking for data impact reports in PRs to validate code changes and automate data migrations with SQL translation and data reconciliation tests.
Comprehensive data observability platform with data validation, data profiling, column-level data lineage, a data catalog, and a business glossary.
Best for enterprises looking for a data quality tool that can be easily self-hosted with a Docker deployment.
Data product platform to build data marketplaces with data contracts based on the Open Data Contract Standard (ODCS), the open-source Data Contract CLI, and data policy checks.
Best for organizations looking to build a data product marketplace with data policy checks.
Want to go deeper?
Read the complete data quality tool market guide — features, pricing, and how to choose.
Read the data quality guide