Dango

Open-source data platform for small teams.

Dango gives you a complete data stack — ingestion, warehouse, transformations, and dashboards — with the operational machinery a self-assembled stack doesn't have: sync queue management, lock recovery, empty-replace protection, schema drift detection, credential health checks, and backups. 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 and dbt docs)

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.

Use Dango with your coding agent

dango mcp setup

Connects Claude Code, Cursor, or Windsurf to your project over MCP — your agent can set up sources (credentials stay in your .env, never in the chat), sync, build and document dbt models, manage schedules, check PII findings and schema drift, diagnose failures, and run read-only queries with PII columns masked. Remote tools default to a dry run. See the full guide for the complete tool reference and worked examples.

Features

• 35 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
• Data catalog — browse tables, columns, and profiling stats; view dbt lineage and test results
• Web dashboard — monitor syncs, manage sources, and view platform health
• Metabase integration — dashboards and SQL queries, auto-configured and ready to use
• Scripts — schedule custom Python scripts alongside your syncs; runs on a schedule with access to your warehouse
• 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 queued execution, retry, and timeout handling
• Webhooks — Slack notifications for sync results and alerts
• Local backup — dango backup lists and restores local project backups
• 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.

Known limitations

Dango is honest about what it doesn't do yet. The short version — full detail at docs.getdango.dev/reference/limitations:

• Single-writer concurrency until the Quack migration lands (DuckDB 2.0)
• No streaming, CDC, or reverse ETL
• 35 sources today, added on demand
• BYOS deployments need to configure their own backup destination (warned at deploy time)

Links

• PyPI
• Changelog
• Issues