skillfed

dagster-fivetran

Package for integrating Fivetran with Dagster.

dagster-fivetran v0.29.18 101.5K downloads/30d#12,933 on PyPI15,996
Permissive license Apache-2.0 Active released

What it is and what it does

dagster-fivetran bridges Fivetran's managed data connectors with Dagster's orchestration and asset management system. It allows you to define Fivetran-sourced data as Dagster assets using a declarative Python interface, so that data ingestion becomes part of your broader data pipeline orchestration rather than a separate system.

The package wraps Fivetran's connector and destination APIs into Dagster asset definitions, enabling you to schedule syncs, track lineage, monitor data quality, and coordinate Fivetran ingestion with downstream transformations—all within Dagster's unified control plane. It is designed for teams already using Dagster for orchestration who want to integrate Fivetran-managed connectors without building custom API wrappers.

Use it for:

  • Orchestrate Fivetran connector syncs as part of a larger Dagster data pipeline, triggering downstream transformations automatically.
  • Track data lineage from Fivetran sources through to final assets, maintaining end-to-end observability in Dagster's UI.
  • Coordinate multiple Fivetran connectors and destinations within a single Dagster job, managing dependencies and scheduling.
  • Define Fivetran-sourced tables as reusable Dagster assets for consumption by analytics, ML, or reporting workflows.
  • Monitor Fivetran sync health and performance through Dagster's built-in observability and alerting framework.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Integrates Fivetran data connectors with Dagster's orchestration engine, enabling declarative asset definitions that automatically sync data from Fivetran sources.

Yes, if you are already using Dagster for orchestration and have Fivetran connectors you want to integrate into your asset graph. The package is actively maintained, has no known vulnerabilities, and low install friction. If you are not yet using Dagster or do not use Fivetran, it has no value.

Install

dagster-fivetran on PyPI

pip

pip install dagster-fivetran

uv

uv add dagster-fivetran

poetry

poetry add dagster-fivetran

Installing dagster-fivetran

Before you install

Low install friction with a single runtime dependency on dagster. The package is actively maintained with a release on 2026-08-14 and no known vulnerabilities.

License in practice

Apache-2.0 licensed, permissive terms allow commercial use, modification, and distribution with minimal restrictions—suitable for most production environments.

Quickstart

pip install dagster-fivetran

import dagster as dg
from dagster_fivetran import build_fivetran_assets

fivetran_assets = build_fivetran_assets(
    connector_id="your_connector_id",
    destination_id="your_destination_id"
)

Requires Python 3.10 or later (up to 3.14); dagster must be installed as the sole runtime dependency.

Verify before relying

  • Specific Fivetran API authentication method and credential handling requirements.
  • Whether the package supports incremental syncs or only full refreshes.
  • Supported Fivetran destination types and any limitations.
  • Performance characteristics for large-scale data volumes or connector counts.

Package facts

License Apache-2.0 (permissive)
Python support supports the current Python release (<3.15,>=3.10)
Install friction low — pure-Python wheel
Runtime dependencies 1 — dagster
Maintenance actively maintained — 0 days since the last release
Last repo commit
First released
Downloads 101,455/month — #12,933 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: dagster_fivetran-0.29.18-py3-none-any.whl

Tags

fivetran dagster integrationfivetran data pipeline orchestrationdagster fivetran assetsautomated data sync orchestrationfivetran connector managementdagster data ingestionfivetran asset materialization
data-orchestrationfivetran-integrationetl

More Distributed Computing packages