dbt-databricks
The Databricks adapter plugin for dbt
Decision gist · record as of 2026-08-14
Yes. dbt-databricks is actively maintained, has no known vulnerabilities, and is the recommended adapter for dbt projects on Databricks. It has low install friction, permissive licensing, and integrates deeply with Databricks' native features. Install it if you are building dbt workflows on Databricks.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or above; requires a Databricks workspace with SQL or runtime 9.1 LTS or later, plus valid credentials.
- Low install friction with a pure-Python wheel.
- The adapter is actively maintained with a recent release and depends on well-established dbt ecosystem packages plus Databricks' own SDKs.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 is permissive; you can use this adapter in commercial projects, modify it, and distribute it freely as long as you include the license notice.
last release 2026-08-12 (2 days) · last repo commit 2026-08-14 · 372 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 9,200,485 downloads/mo, #1,554 on PyPI
Alternatives
Verify before relying
pip install dbt-databricks
# In your dbt profile (profiles.yml):
your_profile_name:
target: dev
outputs:
dev:
type: databricks
schema: [database/schema name]
host: [your.databrickshost.com]
http_path: [/sql/your/http/path]
token: [dapiXXXXXXXXXXXXXXXXXXXXXXX]- Performance characteristics when using Photon execution engine compared to standard Spark.
- Limitations when mixing SQL and Python models in the same dbt project on Databricks.
- Support scope for Databricks runtime releases beyond 9.1 LTS.
What it is and what it does
dbt-databricks is a plugin that connects the dbt data transformation framework to Databricks, allowing data analysts and engineers to build, test, and deploy SQL and Python transformations on the Databricks Lakehouse platform. It abstracts away the complexity of Databricks-specific SQL dialects and connection management, letting you write dbt models that compile to optimized Databricks SQL and Python code.
The adapter is purpose-built for Databricks rather than generic Spark, which means it takes advantage of Databricks-native features: Delta tables as the default format, Unity Catalog's three-level namespace (catalog/schema/relation) for governance, and the Photon vectorized execution engine for performance. It depends on dbt-core, dbt-spark, dbt-adapters, and Databricks' own Python SDKs to handle authentication, query execution, and metadata management.
Use it for
- Build and version-control dbt projects that transform data in Databricks using Delta tables and incremental materializations.
- Organize multi-team data pipelines across catalogs and schemas using Unity Catalog's governance model.
- Mix SQL and Python models in a single dbt project, routing Python models to specific compute via configuration.
- Integrate dbt-databricks into CI/CD workflows or Databricks Jobs for automated data transformation runs.
- Load external data (e.g., from S3) into Delta tables using dbt macros like databricks_copy_into.
- Run data transformation workloads on Databricks with native Photon execution acceleration.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
dbt-databricks is actively maintained, has no known vulnerabilities, and is the recommended adapter for dbt projects on Databricks. It has low install friction, permissive licensing, and integrates deeply with Databricks' native features. Install it if you are building dbt workflows on Databricks.
Install
dbt-databricks on PyPI
Before you install
Low install friction with a pure-Python wheel. The adapter is actively maintained with a recent release and depends on well-established dbt ecosystem packages plus Databricks' own SDKs.
Requires Python 3.10 or above; requires a Databricks workspace with SQL or runtime 9.1 LTS or later, plus valid credentials.
License in practice
Apache-2.0 is permissive; you can use this adapter in commercial projects, modify it, and distribute it freely as long as you include the license notice.
Quickstart
pip install dbt-databricks
# In your dbt profile (profiles.yml):
your_profile_name:
target: dev
outputs:
dev:
type: databricks
schema: [database/schema name]
host: [your.databrickshost.com]
http_path: [/sql/your/http/path]
token: [dapiXXXXXXXXXXXXXXXXXXXXXXX]Verify before relying
- Performance characteristics when using Photon execution engine compared to standard Spark.
- Limitations when mixing SQL and Python models in the same dbt project on Databricks.
- Support scope for Databricks runtime releases beyond 9.1 LTS.
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 packagesclickdatabricks-sdkdatabricks-sql-connectordbt-adaptersdbt-commondbt-coredbt-sparkpackagingpydantic |
| Maintenance | Actively maintained 2 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 9,200,485 / month, #1,554 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/StableLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: dbt_databricks-1.12.4-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “dbt adapter for databricks”
- dbt-databricksdbt-databricks is a dbt adapter that enables data transformation…
- dbt-adaptersProvides base adapter protocols and shared functionality that…
- dbt-commonProvides shared utilities and common code used by dbt-core and dbt…
Give your agent the search over MCP, or paste the wish link into any chat.
More Database packages
psycopg2-binary is a PostgreSQL database adapter for Python that implements the DB API 2.0 specification, enabling Python applications to connect to and query PostgreSQL databases with thread-safe concurrent operations.
Python client library for connecting to and executing commands against Redis key-value stores, supporting both synchronous and asynchronous operations.
Install it if your application needs to interact with Redis; the only prerequisite is a running Redis server instance.
YDB Python SDK is the official client library for connecting to and querying YDB databases from Python applications.
Install it if you need to connect Python applications to YDB databases.
Connects Python applications to Snowflake data warehouses using the DB API 2.0 specification, enabling SQL queries, data transfers, and warehouse operations.
sqlparse tokenizes SQL text into a tree of statements, clauses, and expressions, and provides functions to split scripts, format queries, and inspect parsed tokens without validating dialect or syntax.
Install it if you need to manipulate, format, or analyze SQL text programmatically.
Provides base adapter protocols and shared functionality that database adapters use to integrate with dbt-core, handling connections, dialect translation, relation caching, and core interface management.
See also dbl-discoverx · dbt-spark · dbldatagen · databricks-labs-remorph · databricks-labs-lsql · dbt-clickhouse · dbt-fabricspark · databricks-sql · dbt-athena-community · databricks-dlt