apache-airflow-providers-databricks
Provider package apache-airflow-providers-databricks for Apache Airflow
Decision gist · record as of 2026-08-14
Yes, if you run Apache Airflow and need to orchestrate Databricks workloads. The package is actively maintained, permissively licensed, has low install friction, and carries no known vulnerabilities. It is a standard choice for teams integrating Databricks into Airflow-based data platforms. Install only if you have an existing Airflow deployment and Databricks workspace to connect.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 a configured Databricks connection in Airflow (typically via environment variables or Airflow's connection UI).
- Low friction install as a wheel package.
- Active maintenance with a release 6 days old; the parent Apache Airflow project has strong community backing (46475 stars).
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows use in most commercial and open-source projects without significant legal constraints.
last release 2026-08-08 (6 days) · last repo commit 2026-08-14 · 46,475 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 23,282,118 downloads/mo, #952 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-databricks
from airflow.providers.databricks.operators.databricks_sql import DatabricksSqlOperator
from airflow import DAG
from datetime import datetime
with DAG('databricks_example', start_date=datetime(2026, 1, 1)) as dag:
query_task = DatabricksSqlOperator(
task_id='run_query',
sql='SELECT * FROM my_table',
databricks_conn_id='databricks_default'
)- Whether the package includes all Databricks API operations or a subset of common use cases
- Performance characteristics when orchestrating large-scale or high-frequency Databricks workloads
- Support status for Databricks workspace configurations beyond standard SQL and job execution
What it is and what it does
This is an Apache Airflow provider package that bridges Airflow and Databricks, allowing you to define and run Databricks jobs, SQL queries, and data operations as part of Airflow workflows. It supplies operators, hooks, and sensors that handle authentication, job submission, and result retrieval, so you can treat Databricks compute as a native Airflow task.
The package depends on apache-airflow (>=2.11.0), databricks-sql-connector, requests, aiohttp, pandas, and pyarrow. It's designed for teams already running Airflow who need to orchestrate Databricks workloads alongside other data pipeline tasks. Installation is straightforward via pip, and it supports Python 3.10 through 3.14.
Use it for
- Schedule and monitor Databricks SQL queries as part of multi-step Airflow DAGs
- Trigger Databricks jobs from Airflow and wait for completion before downstream tasks
- Build data pipelines that combine Databricks compute with other Airflow-integrated services (AWS, GCP, etc.)
- Orchestrate ETL workflows where Databricks handles transformation and Airflow coordinates the overall pipeline
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you run Apache Airflow and need to orchestrate Databricks workloads.
The package is actively maintained, permissively licensed, has low install friction, and carries no known vulnerabilities. It is a standard choice for teams integrating Databricks into Airflow-based data platforms. Install only if you have an existing Airflow deployment and Databricks workspace to connect.
Install
apache-airflow-providers-databricks on PyPI
Before you install
Low friction install as a wheel package. Active maintenance with a release 6 days old; the parent Apache Airflow project has strong community backing (46475 stars). Requires Apache Airflow >=2.11.0 and modern Python (3.10–3.14).
Requires an existing Apache Airflow installation (>=2.11.0) and a configured Databricks connection in Airflow (typically via environment variables or Airflow's connection UI).
License in practice
Apache-2.0 permissive license allows use in most commercial and open-source projects without significant legal constraints.
Quickstart
pip install apache-airflow-providers-databricks
from airflow.providers.databricks.operators.databricks_sql import DatabricksSqlOperator
from airflow import DAG
from datetime import datetime
with DAG('databricks_example', start_date=datetime(2026, 1, 1)) as dag:
query_task = DatabricksSqlOperator(
task_id='run_query',
sql='SELECT * FROM my_table',
databricks_conn_id='databricks_default'
)Verify before relying
- Whether the package includes all Databricks API operations or a subset of common use cases
- Performance characteristics when orchestrating large-scale or high-frequency Databricks workloads
- Support status for Databricks workspace configurations beyond standard SQL and job execution
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 9 packagesapache-airflowapache-airflow-providers-common-compatapache-airflow-providers-common-sqlrequestsdatabricks-sql-connectoraiohttpmergedeeppandaspyarrow |
| Maintenance | Actively maintained 6 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 23,282,118 / month, #952 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_databricks-7.18.1-py3-none-any.whl
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See also apache-airflow-providers-dbt-cloud · apache-airflow-providers-oracle · apache-airflow-providers-trino · apache-airflow-providers-microsoft-azure · apache-airflow-providers-apache-hdfs · apache-airflow-providers-presto · altimate-datapilot-cli · apache-airflow-providers-amazon · apache-airflow-providers-mysql · apache-airflow-providers-salesforce