Data Contract CLI
Open-source command-line tool for ODCS data contracts that tests files on ADLS Gen2 with a connection string, storage account key, or service principal.
Best for teams that want Azure Data Lake Storage data tested against vendor-neutral ODCS data contracts in CI/CD with one command.
Collate
Managed agentic data platform built on OpenMetadata, with AI agents, data quality tests, observability metrics, column-level lineage, and governance workflows.
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.
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.
Best for large organizations that want enterprise data quality, master data management, and data governance from one vendor.
Monte Carlo
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.
Acceldata
Autonomous data and AI platform, born in data observability, with AI agents for data monitoring, lineage, governance, and cost optimization.
Best for large enterprises with hybrid or on-premise data estates that want observability, FinOps, and agentic data management from one vendor.
Pantomath
AI-powered data operations center with data and pipeline observability, cross-platform pipeline lineage, and automated root-cause analysis.
Best for data operations teams that need to trace failures across pipelines and route incidents to Jira or ServiceNow.
Anomalo
Autonomous data quality monitoring platform where AI agents monitor, investigate, and report issues across structured and unstructured data.
Best for enterprises that want ML-based monitoring with little rule-writing, including quality checks on unstructured data such as documents.
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.
Best for enterprises in regulated industries that need high test coverage without hand-writing rules, and on-premise deployment via Kubernetes.
Datafold
AI-powered data engineering platform with agents for migrations and code reviews, plus data diff, impact analysis, and anomaly detection.
Best for data teams planning a warehouse migration or wanting data diffs in every pull request to catch regressions before merge.
Decube
Data observability, quality, and lineage platform that links data monitors to column-level lineage, a data catalog, and access control to show business impact.
Best for data teams that want observability, a data catalog, and data governance in the same tool.
Great Expectations
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.
DQLabs
AI-native platform combining data observability, data quality checks, and business context, with anomaly detection, end-to-end lineage, and pipeline observability.
Best for enterprises that want data quality and observability in one tool, connected to their data catalog and issue management tools.
Related integrations
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By Ari Bajo - Data Engineer turned Writer.