Looking for the best data quality tools for Fivetran? This list covers 9 tools that natively integrate with Fivetran — from data testing and data observability to shift-left data quality and unified platforms.
Each tool below links directly to its Fivetran 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.
Leading data observability platform with data monitors, anomaly detection, customizable data quality dashboards, and column-level lineage.
Best for data teams with a big budget looking for a mature and customizable data observability platform that also offers AI observability.
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.
Automated data operations platform with data observability, pipeline observability, end-to-end pipeline lineage, and incident management.
Best for data operations teams looking for end-to-end data pipeline lineage with automated root-cause analysis and integrations with Jira or ServiceNow.
Open-source dbt package to add data observability to dbt projects with anomaly detection tests and a local data observability report generated via CLI.
Best for data analytics teams using dbt looking to add anomaly detection monitors to their existing dbt codebase without a cloud account.
End-to-end data observability platform with data monitors and column-level lineage from data sources to BI dashboards.
Best for data analytics teams with a modern data stack looking to quickly add anomaly detection monitors through the UI.
Data management platform with source code analysis, data impact reports, column-level data lineage to BI, and data contracts.
Best for data teams looking to prevent data quality incidents with data impact reports integrated within their development lifecycle through Git and PRs.
Managed enterprise data platform built on OpenMetadata with data discovery, observability metrics, column-level lineage, and governance workflows.
Best for data teams looking for a fully managed enterprise version of OpenMetadata with dedicated support, security features, and advanced governance worflows.
Managed data observability platform with advanced anomaly detection monitors, column-level lineage, incident management, a data catalog, and AI agents.
Best for data analytics teams using dbt looking for a managed observability platform with team collaboration features and AI-powered issue resolution.
AI-augmented data observability platform with data monitors, end-to-end data lineage, incident management with business context, and a data catalog.
Best for data teams looking to collaborate with business users through integrated data observability, data lineage, and a data catalog for cloud data warehouses.
Unified data trust platform with data monitoring, pipeline monitoring, a data catalog, column-level lineage, and data access control.
Best for data teams looking to combine data observability, a data catalog, and data governance in the same tool.
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By Ari Bajo - Data Engineer turned Writer.