DataOps TestGen is an open-source data quality tool that profiles tables, generates tests from the profiling results, and runs them on a schedule with freshness, volume, and schema monitoring.
The open-source edition includes the full web UI, not just a library. You also get a REST API and an MCP server, so you can drive TestGen from your pipelines or an AI assistant. It is Apache 2.0 licensed and runs the same core engine and UI as TestGen Enterprise.
Interactive Product Tour | Product page | Documentation
- Profiles every column in a table group and records type-specific statistics.
- Flags hygiene issues in new data, so you can review a dataset before it reaches production and send problems back to the supplier.
- Generates data quality validation tests from the profile. You can add your own SQL tests too.
- Runs tests on a schedule, as SQL inside your database. Your data stays where it is.
- Watches each table between test runs with freshness, volume, and schema monitors.
- Gives you one place to manage data quality across datasets, locations, and teams.
As of TestGen 5.134.0, TestGen connects to 14 databases:
- Snowflake
- Databricks SQL
- DuckDB
- 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
- Salesforce Data 360
TestGen also reads CSV, Parquet, and JSON files on a local path, in Amazon S3, or in Azure Blob Storage, with no database in front. Every source works in both the open-source and Enterprise editions.
To set up a connection, see Connect your data.
The dk-installer program installs TestGen in either Docker or pip mode.
You need 2 CPUs, 8 GB memory, 20 GB disk space. pip mode needs Python 3.9+ to run the installer. Docker mode also needs Docker 27+ and Docker Compose 5.0+.
Download the installer into a new, empty directory:
curl -o dk-installer.py 'https://raw.githubusercontent.com/DataKitchen/data-observability-installer/main/dk-installer.py'On Windows, you can instead download dk-installer.exe and double-click it.
Install TestGen:
python3 dk-installer.py tg installThe installer checks for Docker and asks you to pick Docker or pip. Pass --docker or --pip to skip the prompt. When it finishes, it writes credentials to dk-tg-credentials.txt, generates demo data, and opens the TestGen UI in your browser. Use --no-demo to skip the demo data.
Upgrade later with python3 dk-installer.py tg upgrade. Restart with python3 dk-installer.py tg start.
For complete instructions, see the documentation:
Then walk through the Data Observability Overview Demo, and connect your own database.
TestGen ships a Model Context Protocol (MCP) server in the open-source edition. Connect Claude, Claude Code, Cursor, GitHub Copilot, or any MCP client, and ask about your data in plain English. The assistant can profile tables, generate and run tests, and triage failures. Every tool runs under your own TestGen role, so the assistant can do only what you can do.
The installer serves the API and MCP server on port 8530 by default. Change it with --api-port.
Setup instructions: docs.datakitchen.io/testgen/mcp
The core profiling, testing, and monitoring engine is free and open source, with unlimited tables and unlimited data volume. Enterprise adds team access, security, Commercial Pharma tests, source-data controls for AI, and support.
| Open source | Enterprise | |
|---|---|---|
| License | Apache 2.0 | Commercial |
| Users | 1 | Unlimited, $100 per user per month |
| Database connections | 1 | Unlimited, $100 per connection per month |
| Projects | 1 | Unlimited |
| Enterprise security | Included | |
| Commercial Pharma test types (12) | Included | |
| Hide source data from AI clients (MCP) | Included | |
| Support | Community Slack | DataKitchen support |
See datakitchen.io/pricing for current pricing.
- DataOps TestGen documentation
- DataOps TestGen product page
- Configuration (environment variables)
- Local development
Talk with other data practitioners who build with DataKitchen. Share what you know, get help, and contribute.
- Join us on Slack. This is also how you get support: post in the
#supportchannel. - Star us on GitHub
- Follow us on X
- Follow us on LinkedIn
- Get free DataOps certification
- Read our blog
- Sign The DataOps Manifesto
- Sign The Data Journey Manifesto
For details on contributing or running the project for development, see the contributing guide.
DataOps TestGen is Apache 2.0 licensed. See LICENSE.