My Data Quality Tools List
Discover the best 36 data quality, data testing, data observability, shift-left data quality, and unified data quality tools with data governance features. The most comprehensive, actionable, and up-to-date list you'll find. Trust me.
By Ari Bajo - Data Engineer turned Writer.
Updated on May 11, 2026
Data Testing Tools
Great Expectations
Open-source Python library with 50+ declarative expectations to validate data in files, SQL databases, data warehouses, and in-memory DataFrames.
Best for data engineering teams looking for a code-first OSS data testing library with a large built-in expectation library and Python extensibility.
Deequ
Open-source Scala library built on Apache Spark to define and verify data quality constraints and profile large datasets at scale.
Best for data engineering teams using Apache Spark looking for a code-first OSS library to define data quality constraints programmatically in Scala or Python.
Google CloudDQ
Cloud-native data validation CLI with YAML-based data quality checks for BigQuery tables and GCS structured data.
Best for data teams looking for a BigQuery-native solution to write reusable SQL checks and consume data quality outputs programmatically.
DQX by Databricks
Data quality framework for Apache Spark with data quality rule generation from profiling results, YAML and Python-based data validation checks, and a data quality dashboard.
Best for Databricks users looking to validate PySpark DataFrames and Tables across Spark Core, Spark Structured Streaming, and Lakeflow Pipelines / DLT.
Data Observability Tools
Elementary OSS
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.
DataKitchen
Open-source data testing and observability platform with automated test generation, data profiling, and anomaly detection.
Best for data teams looking for a cost-effective data testing and observability solution that also offers DataOps training services.
DQOps
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.
AWS Glue Data Quality
Managed data quality platform built on the open-source Deequ framework with data quality rulesets, scheduling, data quality dashboards, and anomaly detection.
Best for data teams using the AWS Glue Data Catalog and AWS Glue ETL jobs that want to monitor data quality at rest and in transit, with the possibility to quarantine data.
Monte Carlo
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.
DQLabs
Unified data quality and observability platform with anomaly detection, data quality checks, end-to-end data lineage, and pipeline observability.
Best for enterprises looking for unified data quality and observability that integrates with modern data catalogs and issue management tools.
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By Ari Bajo - Data Engineer turned Writer.
Qualytics
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.
Metaplane by Datadog
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.
Anomalo
Automated data quality monitoring platform with UI-based anomaly detection tests for structured and unstructured data.
Best for data teams looking for a specialized data quality monitoring tool that integrates with specialized and cloud-native data catalog tools.
Acceldata
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.
Validio
Real-time data observability platform with window-based data validators, end-to-end data lineage, and incident management.
Best for data teams looking for real-time anomaly detection in data streams, lakes, and warehouses.
Lightup
Data observability platform with data profiling, metrics, anomaly detection monitors, table-level lineage, and incident management.
Best for data teams looking for efficient and scalable window-based metrics for data warehouses monitoring with integrations with data catalogs and issue management tools.
Telmai
Real-time data observability platform for data lakes with anomaly detection, data health reports, and incident management.
Best for data teams looking for data observability for data lakes and data lakehouses with native support for Apache Iceberg, Hudi, and Delta Lake.
Unravel
Agentic data observability and FinOps platform for the cloud with integrations with external data quality checks, cost optimization, incident management, and resolution.
Best for data and infrastructure teams that want to combine data quality results with costs and performance insights into one platform with optimization recommendations.
Pantomath
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.
IBM Databand
Data pipeline and data warehouse monitoring platform with data pipeline job monitors, schema change monitors, custom SQL monitors, alerts, and task-based data lineage.
Best for data teams looking for end-to-end ETL pipeline monitoring with tasks that span across dbt, Airlfow, Azure Data Factory, Spark, IBM DataStage, and IBM Watsonx Data.
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.
Coalesce Data Quality
Data observability product by Coalesce after having acquired SYNQ with UI-based data monitors, column-level lineage, and incident management workflows.
Best for Coalesce users that want to unify data transformation, data catalog and data quality in one product.
Shift-Left Data Quality Tools
Soda Core
Open-source Python library and CLI to write data quality checks and contracts in YAML using SodaCL with 25+ built-in metrics for data warehouses and files.
Best for data engineering teams looking for a YAML-based OSS data testing library that embeds directly in pipelines and CI/CD workflows without a cloud account.
Soda Cloud
Managed data quality platform built on Soda Core with data observability monitors, data contracts, scheduling, and bi-directional integrations with data governance tools.
Best for data engineering teams looking to embed tests at every pipeline stage, quarantine failed records, and integrate bi-directionally with data governance tools.
Gable
Shift left data platform with data contracts, static code analysis, and CI/CD integrations.
Best for data operations teams looking to prevent bad data during CI/CD in database tables, files, Kafka topics, or Protobuf messages.
Foundational
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.
Entropy Data
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.
Datafold
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.
Recce
Open-source dbt validation toolkit to compare environments locally with column-level data impact reports and data-diff views before pushing to CI. Recce Cloud automates these impact reports directly in pull requests.
Best for data analytics teams using dbt looking to validate code changes with data impact reports. The OSS version works locally before pushing to CI; Recce Cloud automates impact reports on every PR without manual setup.
Unified Data Quality Tools
OpenMetadata
Open-source unified metadata platform with data discovery, data quality checks, observability metrics, column-level lineage, and governance workflows.
Best for data teams looking for a self-hosted open-source platform covering data discovery, observability, and governance with a wide range of connector integrations.
Collate
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.
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.
Elementary Cloud
Managed data observability platform built on the Elementary OSS dbt package 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 advanced anomaly detection, team collaboration, and AI-powered issue resolution.
Sifflet
AI-augmented data observability platform with data monitors, column-level data lineage, incident management, and a data catalog.
Best for data analytics teams looking for full-featured data observability, data lineage, and a data catalog in the same tool with integrations for cloud data warehouses.
Bigeye
Lineage-enabled data observability platform with data quality metrics monitoring, anomaly detection, a data catalog, and end-to-end data lineage.
Best for data teams looking to add code-based data observability for a mix of modern and legacy data warehouses and ETLs.
Decube
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.
SelectZero
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.
Ataccama ONE
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.