sqlalchemy-databricks
SQLAlchemy Dialect for Databricks
Decision gist · record as of 2026-08-14
No. The package is abandoned (last update 2022-05-06, archived repository) and has not been maintained since its initial release window. While it has low install friction and permissive MIT licensing, the lack of maintenance creates a high risk of incompatibility with current Databricks and SQLAlchemy versions. For new projects, prefer the official databricks-sql-connector directly or check whether Databricks or the SQLAlchemy community now provide a maintained dialect.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a Databricks account with a valid token and cluster HTTP path; databricks-sql-connector and SQLAlchemy must be installed as runtime dependencies.
- Installation is straightforward with low friction.
- However, the package is archived and abandoned as of 2023-05-15, with no maintenance activity since its last release on 2022-05-06.
License · maintenance · safety
MIT (permissive) — MIT license is permissive and places no restrictions on use, modification, or distribution in commercial or private projects.
last release 2022-05-06 (1561 days) · last repo commit 2023-05-15 · 20 stars · archived
0 known vulnerabilities (OSV.dev, 2026-08-14) · 469,236 downloads/mo, #6,489 on PyPI
Alternatives
Verify before relying
pip install sqlalchemy-databricks
from sqlalchemy import create_engine
engine = create_engine(
"databricks+connector://token:<token>@<host>:443/<database>",
connect_args={"http_path": "<cluster_path>"}
)- Compatibility with current Databricks SQL connector and SQLAlchemy versions given the package's abandoned status.
- Whether the dialect works reliably with Python 3.10 despite no recent maintenance.
- Current viability for production use given the archived repository status.
What it is and what it does
sqlalchemy-databricks is a SQLAlchemy dialect that registers the `databricks+connector` driver, allowing you to use SQLAlchemy's ORM and query tools against Databricks clusters. It wraps the official databricks-sql-connector to provide standard SQLAlchemy connection and table introspection APIs.
The package is designed for developers who want to query Databricks using SQLAlchemy's familiar syntax rather than raw SQL. It supports both workspace and SQL analytics clusters through a standard connection URL pattern. However, the project is archived and has received no updates since 2022-05-06, meaning it may not work with recent versions of its dependencies or Databricks platform changes.
Use it for
- Building Python applications that query Databricks tables using SQLAlchemy ORM without writing raw SQL.
- Migrating existing SQLAlchemy code from other databases to Databricks with minimal refactoring.
- Automating table discovery and metadata inspection on Databricks clusters via SQLAlchemy's reflection API.
- Prototyping data pipelines that read from Databricks using standard SQLAlchemy patterns.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No.
The package is abandoned (last update 2022-05-06, archived repository) and has not been maintained since its initial release window. While it has low install friction and permissive MIT licensing, the lack of maintenance creates a high risk of incompatibility with current Databricks and SQLAlchemy versions. For new projects, prefer the official databricks-sql-connector directly or check whether Databricks or the SQLAlchemy community now provide a maintained dialect.
Install
sqlalchemy-databricks on PyPI
Before you install
Installation is straightforward with low friction. However, the package is archived and abandoned as of 2023-05-15, with no maintenance activity since its last release on 2022-05-06. Relying on it for new projects carries significant risk of incompatibility with future Databricks or SQLAlchemy releases.
Requires a Databricks account with a valid token and cluster HTTP path; databricks-sql-connector and SQLAlchemy must be installed as runtime dependencies.
License in practice
MIT license is permissive and places no restrictions on use, modification, or distribution in commercial or private projects.
Quickstart
pip install sqlalchemy-databricks
from sqlalchemy import create_engine
engine = create_engine(
"databricks+connector://token:<token>@<host>:443/<database>",
connect_args={"http_path": "<cluster_path>"}
)Verify before relying
- Compatibility with current Databricks SQL connector and SQLAlchemy versions given the package's abandoned status.
- Whether the dialect works reliably with Python 3.10 despite no recent maintenance.
- Current viability for production use given the archived repository status.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.8,<4.0 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesdatabricks-sql-connectorSQLAlchemyPyHive |
| Maintenance | Abandoned 1,561 days since the last release |
| Last repo commit | repository archived |
| First released | |
| Downloads | 469,236 / month, #6,489 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseNatural Language :: EnglishProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonTopic :: DatabaseTopic :: Database :: Front-Ends |
Evidence: sqlalchemy_databricks-0.2.0-py3-none-any.whl
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See also databricks-dbapi · databricks-sql-connector · databricks-sqlalchemy · pinotdb · databricks-labs-remorph · databricks-sql · sqlalchemy-pytds · sqlalchemy_exasol · sqlalchemy-hana · starrocks