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.
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.
Elementary Cloud
Data & AI control plane by Boomi with anomaly detection monitors, column-level lineage, incident management, a data catalog, and AI agents.
Best for dbt-centric analytics teams that want managed monitoring, lineage, and AI agents for triage on top of their dbt tests.
Elementary OSS
Open-source dbt package by Boomi that adds anomaly detection tests and a CLI-generated data observability report to dbt projects.
Best for dbt teams that want free anomaly detection tests inside their existing dbt project, without a cloud account.
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.
Soda Cloud
AI-native data quality platform with data contracts written in YAML, UI, or AI, anomaly detection, and AI agents that explain and fix data issues.
Best for data teams that want engineers and business users to agree on data contracts in one place and resolve bad data together.
Soda Core
Open-source data contracts engine (Soda 4) to write data quality checks and contracts in YAML and run them in pipelines and CI/CD.
Best for data engineers who prefer YAML over Python for checks and want them running free inside pipelines and CI/CD.
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.
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.
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.
Related integrations
- Data quality tools for Databricks SQL (34)
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- Data quality tools for Google BigQuery (33)
- Data quality tools for Amazon Redshift (32)
- Data quality tools for Oracle DB (22)
- Data quality tools for Azure Synapse (19)
- Data quality tools for Teradata (16)
- Data quality tools for ClickHouse (15)
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By Ari Bajo - Data Engineer turned Writer.