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Reverse ETL for the code-first data stack

Project description

drt logo

drt — data reverse tool

Reverse ETL for the code-first data stack.

CI PyPI License Python

drt syncs data from your data warehouse to external services — declaratively, via YAML and CLI. Think dbt rundrt run. Same developer experience, opposite data direction.

# pip
pip install drt-core          # core (DuckDB included)
pip install drt-core[bigquery]  # + BigQuery

# uv (recommended)
uv add drt-core
uv add drt-core[bigquery]

drt init
drt run --dry-run
drt run

Why drt?

Problem drt's answer
Census/Hightouch are expensive SaaS Free, self-hosted OSS
GUI-first tools don't fit CI/CD CLI + YAML, Git-native
dbt/dlt ecosystem has no reverse leg Same philosophy, same DX
LLM/MCP era makes GUI SaaS overkill LLM-native by design

Quickstart

1. Install

pip install drt-core[bigquery]
# or
uv add drt-core[bigquery]

2. Initialize a project

mkdir my-drt-project && cd my-drt-project
drt init

This creates:

my-drt-project/
├── drt_project.yml   # project config
└── syncs/            # put your sync definitions here

drt init prompts for source type: bigquery, duckdb, or postgres.

3. Create a sync

# syncs/notify_slack.yml
name: notify_slack
description: "Notify Slack on new users"
model: ref('new_users')
destination:
  type: rest_api
  url: "https://hooks.slack.com/services/YOUR/WEBHOOK/URL"
  method: POST
  headers:
    Content-Type: "application/json"
  body_template: |
    { "text": "New user: {{ row.name }} ({{ row.email }})" }
sync:
  mode: full
  batch_size: 100
  rate_limit:
    requests_per_second: 5
  on_error: skip

4. Run

drt run --dry-run        # preview, no data written
drt run                  # run all syncs
drt run --select notify_slack  # run one sync
drt status               # check recent sync results

CLI Reference

drt init                    # initialize project
drt list                    # list sync definitions
drt run                     # run all syncs
drt run --select <name>     # run a specific sync
drt run --dry-run           # dry run
drt validate                # validate sync YAML configs
drt status                  # show recent sync status

Connectors

Type Name Status Install
Source BigQuery ✅ v0.1 pip install drt-core[bigquery]
Source DuckDB ✅ v0.1 (core)
Source PostgreSQL ✅ v0.1 pip install drt-core[postgres]
Source Snowflake 🗓 planned pip install drt-core[snowflake]
Source Redshift 🗓 planned pip install drt-core[redshift]
Source MySQL 🗓 planned pip install drt-core[mysql]
Destination REST API ✅ v0.1 (core)
Destination Slack Incoming Webhook ✅ v0.1 (core)
Destination GitHub Actions (workflow_dispatch) ✅ v0.1 (core)
Destination HubSpot (Contacts / Deals / Companies) ✅ v0.1 (core)
Destination Google Sheets 🗓 v0.3 (core)
Destination Salesforce 🗓 planned (core)
Destination Notion 🗓 planned (core)
Destination Linear 🗓 planned (core)
Destination SendGrid 🗓 planned (core)

Roadmap

Version Focus
v0.1 BigQuery / DuckDB / Postgres sources · REST API / Slack / GitHub Actions / HubSpot destinations · CLI · dry-run
v0.2 Incremental sync (updated_at watermark), state persistence improvements
v0.3 Scheduling (cron-style), Google Sheets connector, Snowflake source
v0.4 MCP Server (uvx drt mcp run), AI Skills
v1.x Rust engine (PyO3)

Ecosystem

drt is designed to work alongside, not against, the modern data stack:

dlt (load) → dbt (transform) → drt (activate)

Contributing

See CONTRIBUTING.md.

Disclaimer

drt is an independent open-source project and is not affiliated with, endorsed by, or sponsored by dbt Labs, dlt-hub, or any other company.

"dbt" is a registered trademark of dbt Labs, Inc. "dlt" is a project maintained by dlt-hub.

drt is designed to complement these tools as part of the modern data stack, but is a separate project with its own codebase and maintainers.

License

Apache 2.0 — see LICENSE.

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