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.
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.
Telmai
AI-based data observability platform for data lakes and lakehouses, with continuous data validation, anomaly detection, and data health reports.
Best for data teams monitoring data lakes and lakehouses with native support for Apache Iceberg, Hudi, and Delta Lake.
DataKitchen
Open-source data quality testing and observability suite of two tools, TestGen and Observability, with auto-generated tests, data profiling, and anomaly detection.
Best for cost-conscious data teams that want to start free with Apache 2.0 tools and upgrade to Enterprise, priced per connection and user.
AWS Glue Data Quality
Managed AWS data quality service built on Deequ, with DQDL rulesets, rule recommendations, and anomaly detection for data lakes and Glue pipelines.
Best for teams on AWS Glue Data Catalog and Glue ETL that want to check data at rest and in transit, and quarantine bad records.
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By Ari Bajo - Data Engineer turned Writer.