dagster-airbyte

What it is and what it does

dagster-airbyte bridges Airbyte's data connectors with Dagster's declarative asset model, allowing you to define data ingestion workflows as Python functions that Dagster orchestrates. It depends on dagster, python-dateutil, and requests, and is designed to fit into Dagster's broader data pipeline orchestration framework—letting you compose Airbyte-sourced data with transformations and other assets in a single, testable codebase.

The package is part of Dagster's growing integration library and is maintained alongside the core Dagster project. It supports Python 3.10 through 3.14 and carries an Apache-2.0 license, making it suitable for both open-source and commercial use.

Use it for:

• Define Airbyte data connectors as Dagster assets to orchestrate recurring data ingestion alongside downstream transformations.
• Build multi-stage data pipelines that combine Airbyte ingestion with Dagster-orchestrated transformations and ML model training.
• Centralize observability and lineage tracking for data flows that start with Airbyte connectors using Dagster's web UI.
• Test data ingestion logic locally during development before deploying to production orchestration.

Worth the install?

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

Integrates Airbyte data connectors with Dagster's orchestration engine to define and run data ingestion assets as part of declarative data pipelines.

Yes. The package has low install friction, active maintenance, no known vulnerabilities, and a permissive license. Install it if you are already using Dagster for orchestration and want to integrate Airbyte connectors as declarative assets; it is not necessary if you are not using Dagster or do not need Airbyte integration.

Install

dagster-airbyte on PyPI

pip install dagster-airbyte

uv add dagster-airbyte

poetry add dagster-airbyte

Installing dagster-airbyte

Before you install

Low install friction with a pure-wheel distribution. Actively maintained with a recent release and strong upstream project health (15996 GitHub stars, active repository).

License in practice

Apache-2.0 permissive license allows use in commercial and proprietary projects without restriction, though derivative works must retain the license notice.

Quickstart

pip install dagster-airbyte

import dagster as dg
from dagster_airbyte import airbyte_asset

@airbyte_asset
def my_data_from_airbyte():
    pass

Requires Python 3.10 or later (up to 3.14). Assumes Airbyte instance is running and accessible; Dagster and its dependencies must be installed.

Verify before relying

• Specific Airbyte connector types and versions supported by this integration version
• Whether Airbyte instance discovery/configuration is automatic or requires manual setup
• Performance characteristics when orchestrating large-scale Airbyte syncs

Package facts

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

Tags

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