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CatalystData Documentation

CatalystData is a data observability platform: it connects to your databases and warehouses, runs data quality checks against them on a schedule, and alerts your team when something breaks — a table stops updating, a column fills with nulls, a foreign key goes stale.

This site covers everything you need to run it: connecting a data source, building checks, reading results, and administering accounts.

What CatalystData does

  • Connects to 11 data sources — SQL Server, Microsoft Fabric, PostgreSQL, MySQL, Snowflake, BigQuery, Redshift, Databricks, DuckDB/MotherDuck, Trino, and SQLite — via ADBC, so no system-level drivers to install on your own machines.
  • Runs data quality checks — 50+ check types across null/uniqueness, referential integrity, freshness, row-count anomalies, format validation, and more — on a schedule or on demand.
  • Discovers checks for you — scan a connection to see its tables and columns, and get suggested checks based on what it finds.
  • Alerts your team — email, webhook, Slack, or Microsoft Teams when a check fails, with rules for how many failures before it fires.
  • Tracks data contracts — versioned schema and check definitions you can validate a table against before trusting it downstream.
  • Keeps a full audit trail and RBAC — owner/editor/viewer roles per account, Microsoft Entra ID single sign-on, and an audit log of who changed what.

Where to start

If you're evaluating CatalystData or setting it up for the first time, start with Getting started — it walks through deploying the stack, signing in, and creating your first connection and check.

If you already have CatalystData running and want to connect a specific database, jump straight to Connect a data source.

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