dagster-databricks
Package for Databricks-specific Dagster framework op and resource components.
Decision gist · record as of 2026-08-14
Yes, if you are already using Dagster and Databricks and want a native integration between them. The package is actively maintained, has no known vulnerabilities, and low install friction. Install only if you need Databricks-specific orchestration components; the base dagster library alone may suffice for simpler use cases.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (supports up to 3.14).
- Requires active Databricks workspace credentials and connection configuration.
- Low friction install with a wheel distribution.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 licensed, permissive terms allowing commercial and private use with minimal restrictions.
last release 2026-08-14 (0 days) · last repo commit 2026-08-14 · 15,996 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 576,517 downloads/mo, #5,928 on PyPI
Alternatives
Verify before relying
pip install dagster-databricks
import dagster as dg
from dagster_databricks import databricks_resource
@dg.asset
def my_table(context):
# Use Databricks resource to query or write data
pass- Whether this package provides Databricks-specific ops/resources beyond what the base dagster library offers
- What specific Databricks operations (SQL, Delta Lake, jobs) are supported by the included components
- Whether additional setup or authentication configuration is needed beyond standard Databricks SDK setup
What it is and what it does
dagster-databricks is a Dagster integration library that bridges Dagster's declarative data orchestration framework with Databricks infrastructure. It provides Databricks-specific ops and resource components that let you build data pipelines as Python functions, with Dagster handling scheduling, lineage tracking, and observability while your code runs against Databricks clusters and SQL warehouses.
The package sits within Dagster's broader ecosystem—you declare data assets using Dagster's programming model, and dagster-databricks handles the Databricks-specific plumbing: authentication, cluster interaction, and job submission. It's designed for teams already using Databricks who want Dagster's asset-centric orchestration, testing, and monitoring capabilities layered on top.
Use it for
- Build and schedule SQL transformations on Databricks Delta Lake tables, with Dagster tracking lineage and data quality.
- Orchestrate multi-step data pipelines that read from Databricks, transform in Python, and write results back to Databricks.
- Run PySpark jobs on Databricks clusters via Dagster, with centralized monitoring and error handling across your data platform.
- Define machine learning training pipelines that pull features from Databricks and log models back to a Databricks workspace.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are already using Dagster and Databricks and want a native integration between them.
The package is actively maintained, has no known vulnerabilities, and low install friction. Install only if you need Databricks-specific orchestration components; the base dagster library alone may suffice for simpler use cases.
Install
dagster-databricks on PyPI
Before you install
Low friction install with a wheel distribution. Actively maintained as of 2026-08-14 with no known vulnerabilities. Depends on dagster and databricks-sdk among other core libraries.
Requires Python 3.10 or later (supports up to 3.14). Requires active Databricks workspace credentials and connection configuration.
License in practice
Apache-2.0 licensed, permissive terms allowing commercial and private use with minimal restrictions.
Quickstart
pip install dagster-databricks
import dagster as dg
from dagster_databricks import databricks_resource
@dg.asset
def my_table(context):
# Use Databricks resource to query or write data
passVerify before relying
- Whether this package provides Databricks-specific ops/resources beyond what the base dagster library offers
- What specific Databricks operations (SQL, Delta Lake, jobs) are supported by the included components
- Whether additional setup or authentication configuration is needed beyond standard Databricks SDK setup
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <3.15,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesaiohttpdagster-pipesdagster-pysparkdagsterdatabricks-sdk |
| Maintenance | Actively maintained 0 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 576,517 / month, #5,928 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: dagster_databricks-0.29.18-py3-none-any.whl
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See also dagster · dagster-dg-core · dagster-docker · dagster-aws · databricks-bundles · dagster-pyspark · dagster-spark · dagster-rest-resources · dagster-cloud-cli · dagster-webserver