apache-airflow-providers-tableau
Provider package apache-airflow-providers-tableau for Apache Airflow
Decision gist · record as of 2026-08-14
Yes. This is a production-stable, actively maintained provider for a widely-used orchestration platform. Install it if you run Airflow and need to automate Tableau operations; the low install friction and permissive license make it a straightforward addition to an existing Airflow deployment. No known security vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an existing Apache Airflow installation (>=2.11.0) and valid Tableau Server or Tableau Cloud credentials configured in Airflow connections.
- Low install friction; a pure-Python wheel with three runtime dependencies.
- Actively maintained with recent releases; the parent Apache Airflow project has strong community backing and 46490 repository stars.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most organizational contexts.
last release 2026-07-10 (35 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,078,987 downloads/mo, #4,400 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-tableau
from airflow.providers.tableau.operators.tableau_server import TableauServerRunQueryOperator
from airflow import DAG
with DAG('tableau_refresh') as dag:
task = TableauServerRunQueryOperator(task_id='refresh_workbook')- Which specific Tableau operations (refresh, publish, permissions) are supported by the operators in this version.
- Whether tableauserverclient >=0.27 supports Tableau Server, Tableau Cloud, or both.
- Performance characteristics when orchestrating large numbers of Tableau jobs in parallel.
What it is and what it does
This is an Apache Airflow provider package that bridges Airflow and Tableau, allowing you to build data pipelines that interact with Tableau Server or Tableau Cloud. It wraps the tableauserverclient library and exposes Tableau operations as Airflow operators and hooks, so you can trigger refreshes, manage workbooks, handle permissions, and coordinate Tableau tasks alongside other pipeline steps in your DAGs.
The package requires Airflow 2.11.0 or later and runs on Python 3.10 through 3.14. It is production-stable and actively maintained by the Apache Airflow community. Installation is straightforward—a single pip command on top of an existing Airflow environment—and carries no unusual system dependencies.
Use it for
- Trigger Tableau workbook refreshes on a schedule or in response to upstream data pipeline events.
- Automate Tableau Server permission and user management as part of infrastructure-as-code workflows.
- Coordinate multi-step ETL pipelines where Tableau publishing or refresh is a downstream task.
- Monitor Tableau job status and integrate Tableau operations into broader Airflow monitoring and alerting.
- Build data lineage workflows that connect data warehouse updates to Tableau dashboard refreshes.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
This is a production-stable, actively maintained provider for a widely-used orchestration platform. Install it if you run Airflow and need to automate Tableau operations; the low install friction and permissive license make it a straightforward addition to an existing Airflow deployment. No known security vulnerabilities.
Install
apache-airflow-providers-tableau on PyPI
Before you install
Low install friction; a pure-Python wheel with three runtime dependencies. Actively maintained with recent releases; the parent Apache Airflow project has strong community backing and 46490 repository stars.
Requires an existing Apache Airflow installation (>=2.11.0) and valid Tableau Server or Tableau Cloud credentials configured in Airflow connections.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most organizational contexts.
Quickstart
pip install apache-airflow-providers-tableau
from airflow.providers.tableau.operators.tableau_server import TableauServerRunQueryOperator
from airflow import DAG
with DAG('tableau_refresh') as dag:
task = TableauServerRunQueryOperator(task_id='refresh_workbook')Verify before relying
- Which specific Tableau operations (refresh, publish, permissions) are supported by the operators in this version.
- Whether tableauserverclient >=0.27 supports Tableau Server, Tableau Cloud, or both.
- Performance characteristics when orchestrating large numbers of Tableau jobs in parallel.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesapache-airflowapache-airflow-providers-common-compattableauserverclient |
| Maintenance | Actively maintained 35 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,078,987 / month, #4,400 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: Web EnvironmentFramework :: Apache AirflowFramework :: Apache Airflow :: ProviderIntended Audience :: DevelopersIntended Audience :: System AdministratorsProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: System :: Monitoring |
Evidence: apache_airflow_providers_tableau-5.6.0-py3-none-any.whl
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See also apache-airflow-providers-arangodb · apache-airflow-providers-yandex · apache-airflow-providers-airbyte · apache-airflow-providers-zendesk · apache-airflow-providers-asana · airflow-provider-great-expectations · tableauserverclient · apache-airflow-providers-apache-iceberg · apache-airflow-providers-neo4j · apache-airflow-providers-papermill