Automated Data Quality Testing

DataOps Data Quality TestGen

Auto-generated data quality tests. Full coverage in minutes, not months. No feature gates. No six-figure platform fees. Your team's data quality should cost an engineer's salary for a month, not years.

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TestGen monitors: freshness, volume, schema, and metric anomalies by table Take the product tour
  • 55data profiling column characteristics
  • 32data hygiene detectors
  • 33test types auto-generated from the profile
  • 14business rule and custom SQL test types

The periodic table of data quality

TestGen's checks, sorted by the data quality dimension each one protects.

Showing all 66 checks. Each tile links to its section in the TestGen documentation.

Key capabilities

Works where your data lives

  • Snowflake
  • Databricks
  • Azure Synapse
  • Azure SQL
  • SQL Server
  • BigQuery
  • Redshift
  • Oracle
  • SAP HANA
  • PostgreSQL

Also supported: Amazon Aurora PostgreSQL, Microsoft OneLake, and Salesforce Data 360. Plus structured data in Apache Iceberg tables and file formats (Parquet, Avro, ORC, CSV, JSON) exposed as external tables, including Amazon Redshift Spectrum and Snowflake external tables.

Why teams choose TestGen

  • You Don't Have Time to Write Tests. TestGen Does It Automatically.

    You're buried in customer requests. You have no time to write tests, let alone innovate. TestGen scans your data and generates the tests and anomaly detectors for you. No coding, no massive YAML configuration.

Open Source with Reasonable Enterprise Pricing

Enterprise pricing is a flat $100 per month per user and database connection, with unlimited tables and data volume. No per-table tax. A year of enterprise data quality costs roughly one data engineer's monthly salary.

See pricing
Enterprise, per user and database connection$100/mo
Open source: one user, one project, one connectionFree

AI & Agents

Your AI assistant can now run your data quality program

TestGen ships a Model Context Protocol (MCP) server: 96 tools that span the whole data quality loop, from "what data do I have" to "email me when the score drops." Connect Claude, Claude Code, Cursor, Copilot, or Databricks Genie and ask in plain English. It's open source under Apache 2.0 and runs behind your firewall, so your warehouse credentials never leave your network.

  • Claude
  • Claude Code
  • Cursor
  • GitHub Copilot
  • Databricks Genie
Get the MCP cheat sheet Read the MCP docs

Ask in plain English

Ask "what data do I have, and how healthy is it?" and get the inventory and a quality score in seconds. Ask "show me the rows behind that" and get the actual records that failed, not a chart about them.

Guided triage

Pre-built prompts turn a wall of overnight failures into a guided conversation. Failures grouped by test and column. What just broke, separated from what's been flaky for six weeks. TestGen records every disposition with an audit trail.

Autonomous, with a human veto

Put an agent on a schedule. It proposes fixes for the boring, repetitive failures like trailing whitespace, case, and ISO codes. Anything that needs judgment gets a ticket instead. Nothing touches your data until you approve it, and TestGen logs every action.

Same data, same security model, a different front door. The MCP server authenticates as you and runs every tool with your existing TestGen role. No per-seat agent tax in either edition.

TestGen versus the competition

Head-to-head comparisons with every major data quality and observability tool. Search for the one you are evaluating.

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See all comparisons →

Frequently asked questions

What databases does TestGen support?

Snowflake, Databricks SQL, Azure Synapse Analytics, Azure SQL Database, Microsoft SQL Server, Microsoft OneLake, Google BigQuery, Amazon Redshift, Amazon Aurora PostgreSQL, Oracle Database 12c and later, SAP HANA, PostgreSQL, and Salesforce Data 360. All are supported in both open source and enterprise. TestGen also works with file-based data (Parquet, Avro, ORC, CSV, JSON) through external table formats like Apache Iceberg, Redshift Spectrum, and Snowflake external tables.

Does TestGen work with file-based data?

Yes. TestGen supports structured file formats including Parquet, Avro, ORC, CSV, and JSON through external table formats. If your data warehouse can expose files as external tables (e.g., Apache Iceberg, Redshift Spectrum, Snowflake external tables), TestGen can profile and test them.

Can I write custom SQL tests?

Yes. TestGen supports two types of custom tests: custom conditions for row-level business rules (e.g., quantity_shipped <= quantity_ordered) and full custom SQL queries for complex joins and cross-table validation. These tests let you extend auto-generated coverage with domain-specific logic.

What's the difference between Open Source and Enterprise?

Open source includes the full testing engine: profiling, auto-generated tests, hygiene detection, anomaly monitoring, quality dashboards, and a built-in UI. It's limited to a single user, single project, and single database connection. Enterprise adds multi-user access with single sign-on (SSO) authentication support, role-based access control, multi-project management, PII masking, custom branding, and dedicated support.

How is pricing structured?

Enterprise pricing is a flat $100 per month per user and database connection, with unlimited tables and data volume. No per-table fees that scale unpredictably as your data grows.

How does TestGen compare to Great Expectations, Soda, or dbt tests?

Those tools require your team to write and maintain tests in Python, YAML, or SQL. TestGen auto-generates tests from your data. No code required. It covers about 80% of data quality testing automatically. You handle the 20% that needs domain judgment. See our vendor comparison page for head-to-heads against every major data quality tool.

Can TestGen work alongside my existing tools?

Yes. TestGen complements your existing data stack. It connects to your databases, runs tests in-place, and integrates results into your workflows. It works alongside orchestrators, BI tools, and data catalogs without replacing any of them.

Start generating tests in minutes

Install open source TestGen today, or request an Enterprise demo.

$ Select a platform above to get started.
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The DataOps Way to Data Quality and Data Observability cover

Free book

Not ready to try it out now? Read the free book.

The DataOps Way to Data Quality and Data Observability covers why data quality keeps failing and what to do about it: culture, testing strategy, monitoring, and the seven deadly sins of AI-generated pipelines.

  • 620 pages
  • 63 chapters
  • Updated September 2026
  • By Chris Bergh, Chip Bloche, and Gil Benghiat
Get the free PDF → Ready to install? Back to the installer ↑