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apache-airflow-providers-teradata

Provider package apache-airflow-providers-teradata for Apache Airflow

Worth itPyPI MonitoringReleased Aug 2026471.9K downloads / moApache-2.0Pure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — apache_airflow_providers_teradata-3.6.2-py3-none-any.whl
v3.6.2 · released 2026-08-08 · Python >=3.10 · 5 runtime deps: apache-airflow, apache-airflow-providers-common-compat, apache-airflow-providers-common-sql, teradatasqlalchemy, teradatasql

Yes. Install this if you are running Apache Airflow and need to orchestrate Teradata database operations. The package is actively maintained, has no known vulnerabilities, carries a permissive Apache-2.0 license, and integrates cleanly with Airflow's provider ecosystem. Verify that your Airflow version meets the >=2.11.0 requirement and that you have Teradata JDBC drivers available in your environment.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires apache-airflow >=2.11.0 and Python >=3.10; Teradata JDBC drivers (teradatasql >=17.20.0.28, teradatasqlalchemy >=17.20.0.0) must be installed and a Teradata connection configured in Airflow.
  • Low friction installation as a pure-Python wheel.
  • Active maintenance with a release 6 days old.

License · maintenance · safety

Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most enterprise and open-source projects.

last release 2026-08-08 (6 days) · last repo commit 2026-08-14 · 46,490 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 471,866 downloads/mo, #6,476 on PyPI

Verify before relying

pip install apache-airflow-providers-teradata

from airflow.providers.teradata.operators.teradata import TeradataOperator
from airflow import DAG

with DAG('my_teradata_dag') as dag:
    task = TeradataOperator(
        task_id='query_teradata',
        sql='SELECT * FROM my_table',
        teradata_conn_id='teradata_default'
    )
  • Whether the package includes specific operators beyond generic SQL execution (e.g., bulk load, export utilities).
  • Performance characteristics and connection pooling behavior under high-volume DAG execution.
  • Support for Teradata-specific authentication methods beyond standard SQL connection strings.
Same gist for agents: .md · .json

What it is and what it does

This is an Apache Airflow provider package that adds Teradata database support to Airflow workflows. It supplies operators, hooks, and connection types that allow you to build data pipelines that query, load, or manage data in Teradata systems as part of your DAG tasks. The package wraps teradatasql and teradatasqlalchemy drivers and integrates with Airflow's common SQL provider framework.

You install it alongside an existing Airflow deployment (>=2.11.0) and configure Teradata connections through Airflow's UI or environment. Once configured, you can use Teradata operators in your DAGs to execute SQL, manage data movement, or orchestrate Teradata-dependent workflows. It supports Python 3.10 through 3.14 and is actively maintained by the Apache Airflow project.

Use it for

  • Schedule and monitor recurring SQL queries or stored procedures against Teradata as part of a larger data pipeline.
  • Load data from external sources into Teradata tables on a scheduled basis using Airflow task orchestration.
  • Build multi-step ETL workflows where Teradata is one of several data sources or destinations.
  • Trigger Teradata operations conditionally based on upstream task results or external events in an Airflow DAG.
  • Integrate Teradata data operations with cloud storage (AWS S3, Azure Blob) using optional cross-provider dependencies.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

Worth it

Yes.

Install this if you are running Apache Airflow and need to orchestrate Teradata database operations. The package is actively maintained, has no known vulnerabilities, carries a permissive Apache-2.0 license, and integrates cleanly with Airflow's provider ecosystem. Verify that your Airflow version meets the >=2.11.0 requirement and that you have Teradata JDBC drivers available in your environment.

Install

apache-airflow-providers-teradata on PyPI

Before you install

Low friction installation as a pure-Python wheel. Active maintenance with a release 6 days old. Depends on apache-airflow (>=2.11.0) and Teradata-specific drivers (teradatasql, teradatasqlalchemy); ensure your Airflow environment meets the minimum version.

Requires apache-airflow >=2.11.0 and Python >=3.10; Teradata JDBC drivers (teradatasql >=17.20.0.28, teradatasqlalchemy >=17.20.0.0) must be installed and a Teradata connection configured in Airflow.

License in practice

Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most enterprise and open-source projects.

Quickstart

pip install apache-airflow-providers-teradata

from airflow.providers.teradata.operators.teradata import TeradataOperator
from airflow import DAG

with DAG('my_teradata_dag') as dag:
    task = TeradataOperator(
        task_id='query_teradata',
        sql='SELECT * FROM my_table',
        teradata_conn_id='teradata_default'
    )

Verify before relying

  • Whether the package includes specific operators beyond generic SQL execution (e.g., bulk load, export utilities).
  • Performance characteristics and connection pooling behavior under high-volume DAG execution.
  • Support for Teradata-specific authentication methods beyond standard SQL connection strings.

Package facts

LicenseApache-2.0 permissive
Python supportSupports the current Python release >=3.10
Install frictionLow. Pure-Python wheel
Runtime dependencies
5 packages
apache-airflowapache-airflow-providers-common-compatapache-airflow-providers-common-sqlteradatasqlalchemyteradatasql
MaintenanceActively maintained 6 days since the last release
Last repo commit
First released
Downloads471,866 / month, #6,476 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone 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_teradata-3.6.2-py3-none-any.whl

Tags

Capabilities
airflow teradata integrationteradata operator airflowairflow teradata connectionteradata sql airflowairflow teradata providerteradata dag tasksairflow database provider
Topics
airflow-providerteradata-integrationdata-orchestration
PyPI keywords
airflow-providerteradataairflowintegration

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See also apache-airflow-providers-postgres · apache-airflow-providers-mysql · apache-airflow-providers-vertica · apache-airflow-providers-common-sql · apache-airflow-providers-databricks · teradatamodelops · apache-airflow-providers-neo4j · apache-airflow-providers-sqlite · teradataml · teradata