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apache-airflow-providers-teradata

library3.6.0pypypi✓ verified 86d ago

The `apache-airflow-providers-teradata` package provides an official Teradata provider for Apache Airflow, enabling interaction with Teradata databases via Airflow DAGs. It includes hooks and operators for executing SQL queries and managing data. The current version is 3.5.2, and it typically releases updates aligned with Airflow's core release cycle or when significant bug fixes/features are added.

workflow database data

pip install apache-airflow-providers-teradata

github ↗package ↗docs ↗changelog ↗

INSTALL

IMPORT

SIG · APACHE-AIRFLOW-PRO

apache-airflow-providers-teradata

workflowpythonv3.6.0

Install

27.7s avg

Import

4818ms

Disk

974MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v3.6.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 4.960s · 972.8MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 27.7s · import 4.675s · 971MB

974MB installed

● package 974MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

TeradataHook

✓ from airflow.providers.teradata.hooks.teradata import TeradataHook

TeradataOperator

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

A simple Airflow DAG that uses the `TeradataOperator` to execute a basic SQL query against a Teradata database. Requires an Airflow connection named `teradata_default` to be configured in the Airflow UI or via environment variables, specifying the Teradata host, port, username, password, and optionally a database.

from __future__ import annotations import pendulum from airflow.models.dag import DAG from airflow.providers.teradata.operators.teradata import TeradataOperator with DAG( dag_id="teradata_example_dag", start_date=pendulum.datetime(2023, 1, 1, tz="UTC"), catchup=False, schedule=None, tags=["teradata", "example"], ) as dag: # This task requires an Airflow connection named 'teradata_default' # configured with appropriate Teradata credentials (host, port, schema, user, password). run_teradata_query = TeradataOperator( task_id="run_simple_query", sql="SELECT 1;", teradata_conn_id="teradata_default", # Ensure this connection exists in Airflow UI )

Debug

Known issues

gotchaThe `teradata_conn_id` parameter in operators and hooks must correspond to an existing Teradata connection configured in Airflow. Misconfigurations (wrong host, port, credentials) are a common source of failures.

fix

Ensure the connection ID matches, and the Teradata connection in Airflow UI (Admin -> Connections) or environment variables (e.g., AIRFLOW_CONN_TERADATA_DEFAULT) is correctly configured with all necessary parameters like host, port, schema, login, and password.

affects: All versions

gotchaSpecific versions of the `teradatasql` Python driver might be required or recommended for certain Teradata database versions or features. Ensure compatibility, especially when encountering unexpected connection or query execution errors.

fix

Check the `apache-airflow-providers-teradata` GitHub repository or Airflow documentation for any specific `teradatasql` version requirements. If issues arise, try upgrading or downgrading `teradatasql` (`pip install --upgrade teradatasql==X.Y.Z`) or the provider itself.

affects: All versions

gotchaSecure connections using SSL/TLS might require additional configuration parameters in the Airflow connection, such as `ssl_mode` or `ca_cert_path`. If not configured correctly, it can lead to connection failures.

fix

Refer to the `teradatasql` documentation and Airflow Teradata provider documentation for detailed SSL/TLS configuration options. Add relevant parameters to the 'Extra' field of your Airflow Teradata connection.

affects: All versions

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'teradatasql'

The `teradatasql` Python driver, which is a required dependency for the Teradata provider, is not installed in the Airflow environment.

fix

Install the `teradatasql` package: `pip install teradatasql` (or reinstall the provider which pulls it in: `pip install apache-airflow-providers-teradata`).

airflow.exceptions.AirflowException: The teradata_conn_id parameter is missing or invalid.

The `teradata_conn_id` specified in the operator or hook does not exist or is empty. This prevents Airflow from establishing a connection to the Teradata database.

fix

Ensure that the `teradata_conn_id` argument in your operator/hook matches an existing connection ID configured in Airflow. Verify its presence and correctness in the Airflow UI (Admin -> Connections) or environment variables.

teradatasql.OperationalError: [HY000] [2000] Error while connecting to database. (DBMSG: [2000] [HY000] Cannot resolve host name.)

A generic connection error indicating issues reaching the Teradata database. Common causes include incorrect host/port, network firewalls, or the database service being down.

fix

Double-check the host and port specified in your Airflow Teradata connection. Verify network connectivity from your Airflow worker to the Teradata server. Consult your network or database administrator if necessary.

Upgrade

Version history

3.6.0latest on PyPI · released May 23, 2026

Audit

Dependencies

apache-airflowrequiredCore Airflow installation is required for any provider.

teradatasqlrequiredDatabase driver for connecting to Teradata.

Agent activity

40 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/apache/airflow ↗

packagehttps://pypi.org/project/apache-airflow-providers-teradata/ ↗

docshttps://airflow.apache.org/docs/apache-airflow-providers-teradata/3.5.2 ↗

changeloghttps://airflow.apache.org/docs/apache-airflow-providers-teradata/3.5.2/changelog.html ↗