Dango

Open-source data platform for small teams.

Dango gives you a complete data stack — ingestion, warehouse, transformations, and dashboards — in a single CLI. It combines dlt for data loading, DuckDB as the analytics database, dbt for SQL transformations, and Metabase for dashboards. One pip install, one command to start.

Upgrading from v0.1.x? v1.0.0 is a complete rewrite. Back up your data and run dango init to create a new v1 project. See the migration guide for details.

Quick Start

Prerequisites: Python 3.10-3.13, Docker (for Metabase)

mkdir my-project && cd my-project
pip install getdango
dango init
dango start

Open http://localhost:8800 to see your data platform.

Or use the install script:

curl -sSL https://getdango.dev/install.sh | bash

For detailed installation instructions, see the documentation.

Features

• 33 data sources — Stripe, Google Sheets, Google Analytics, Shopify, PostgreSQL, MySQL, CSV, REST APIs, and more
• Auto-generated dbt models — staging models created automatically when you add a source
• Web dashboard — monitor syncs, browse your data catalog, manage sources
• Metabase integration — dashboards and SQL queries, auto-configured and ready to use
• Cloud deployment — deploy to DigitalOcean or any server with dango deploy
• Authentication — admin login, user management, 2FA, API keys
• Schema drift detection — get alerted when source schemas change
• PII scanning — detect personally identifiable information across your tables
• Notebooks — Marimo notebooks connected to your DuckDB warehouse
• Monitoring — metric tracking with trend detection and drill-downs
• Scheduled syncs — cron-based scheduling with retry and timeout handling
• Webhooks — Slack notifications for sync results and alerts
• File watcher — auto-sync when CSV files change on disk

Screenshots

Data Sources page — monitor syncs, row counts, and schedule status for all your data sources.

Data Catalog — browse tables, explore columns with profiling stats, view data lineage.

dbt Models — view model status, run transformations, and track test results.

Architecture

Sources  →  dlt  →  DuckDB  →  dbt  →  Metabase
(APIs,       (load)  (warehouse) (transform) (dashboards)
 CSVs,
 databases)

All data stays local in DuckDB. No external warehouse needed.

Tech Stack

Documentation

Full documentation at docs.getdango.dev.

Contributing

See CONTRIBUTING.md for development setup and guidelines.

License

Apache 2.0 — see LICENSE for details.

Links

• PyPI
• Changelog
• Issues