Documentation
How to install Tabularia on your own infrastructure, connect it to your data, build and orchestrate your work on it, and keep it governed.
Start here
Capabilities
What you can build: visual flows, analysis on any step, AI questions, pixel-perfect reports, dashboards, Python, R and SQL scripts, containers and the orchestration that ties them together.
- All capabilities
- Low-code flows
- Preview and analysis
- Ask your data with AI
- Pixel-perfect reports
- Report functions
- Dashboards
- Python and R
- SQL scripts
- marimo notebooks as apps
- Docker images in flows
- Flow groups: orchestration
- Scheduling
- Pushmail: datasources, reports and dashboards by email
- Dynamic dates
- Engines
- Engine differences
Sources
Every way data comes in: files, databases, buckets, SFTP folders, HTTP APIs, SharePoint, Google Sheets, and the results of your own flows.
Connections
The systems Tabularia reads from and writes to, how each connection is set up, and who may use it.
Integrations
How Tabularia fits your stack: AI providers, the REST API and webhooks, dbt, OpenLineage, single sign-on, SIEM and monitoring.
Security & governance
Who may see and do what, what is recorded, and how data quality and personal data are kept in check.
Install & operate
Run it in production on Kubernetes, configure it, upgrade it and keep it healthy.
Reference
Release process and the remaining reference pages.