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.
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.
Bigeye
Enterprise AI trust platform built on data observability, with anomaly detection, end-to-end lineage, and governance of the data AI agents use.
Best for large enterprises with modern and legacy data sources that also need to govern which data their AI agents access.
DQOps
Open-source data quality operations center to profile, automate, and monitor data quality with built-in checks, monitors, and data quality KPI dashboards.
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.
Best for data teams planning a warehouse migration or wanting data diffs in every pull request to catch regressions before merge.
FirstEigen DataBuck
Zero-code data quality software where AI agents auto-discover rules, validate and reconcile data, and score data trust across sources.
Best for enterprises in regulated industries that need automated data reconciliations and validations across legacy and cloud sources.
Validio
Agentic data quality and observability platform with real-time validators for streams, lakes, and warehouses, end-to-end lineage, and incident management.
Best for data teams that need real-time anomaly detection on data streams like Kafka and Kinesis as well as in warehouses.
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.
SelectZero
Self-hosted data observability platform with value-level data validation, column-level lineage, a data catalog, and a business glossary.
Best for enterprises that cannot let data leave their environment and want one self-hosted tool, deployed with Docker.
Lightup
Enterprise data observability platform with AI anomaly detection, no-code data quality checks, and an agentic interface that works with Claude and Gemini.
Best for enterprises that want business users to set up no-code checks at scale, with integrations for data catalogs and issue management tools.
dbt tests
Data tests built into open-source dbt Core that run as SQL in Teradata through the dbt-teradata adapter: generic tests such as unique and not_null, custom SQL tests, and unit tests.
Best for teams that transform Teradata data with dbt and want free tests next to their models, run in the same CI/CD.
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By Ari Bajo - Data Engineer turned Writer.