databricks-sqlalchemy
Databricks SQLAlchemy plugin for Python
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no known vulnerabilities, low install friction, and a permissive license. Install it if you need to use SQLAlchemy with Databricks. Be aware that LargeBinary, PickleType, Enum types, and CHECK constraints are not yet supported—verify these don't block your schema design before committing.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Databricks workspace with Unity Catalog enabled and valid API token; hive_metastore catalog support is untested.
- Low install friction with a pure-Python wheel distribution.
- Actively maintained as of July 2026 with recent releases.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows use in commercial and open-source projects with minimal restrictions; attribution required.
last release 2026-07-02 (43 days) · last repo commit 2026-07-01 · 25 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 37,744,755 downloads/mo, #721 on PyPI
Alternatives
Verify before relying
pip install databricks-sqlalchemy
from sqlalchemy import create_engine
engine = create_engine(
"databricks://token:dapi***@host.cloud.databricks.com"
"?http_path=/sql/1.0/warehouses/***&catalog=main&schema=default"
)- Whether LargeBinary and PickleType limitations are blocking for your use case (documented as unsupported).
- Whether CHECK constraint and Enum type support roadmap aligns with your schema design needs.
- Compatibility with Databricks SQL connector versions beyond what the package pins.
What it is and what it does
databricks-sqlalchemy is a SQLAlchemy dialect that translates SQLAlchemy's ORM and expression language into Databricks SQL, letting you use familiar Python database patterns against Databricks workspaces. It wraps the databricks_sql_connector driver and integrates with SQLAlchemy's type system, mapping common types like String, Integer, and DateTime to their Databricks equivalents while exposing Databricks-specific types like TINYINT and TIMESTAMP_NTZ.
The package is built for SQLAlchemy 2.0 and workspaces with Unity Catalog enabled. It handles connection pooling, type coercion, and multi-row insert optimization through dialect-specific parameters. You configure it via a connection string that includes your Databricks host, HTTP path, API token, catalog, and schema, then use standard SQLAlchemy patterns—create_engine, declarative models, and query builders—without rewriting for Databricks.
Use it for
- Build Python applications using SQLAlchemy ORM against Databricks without writing native SQL.
- Migrate existing SQLAlchemy applications from other databases to Databricks by changing only the connection string.
- Use pandas DataFrames with to_sql() to load data into Databricks tables via SQLAlchemy.
- Write data pipelines that query Databricks SQL warehouses from Python applications.
- Integrate Databricks with Alembic for schema migrations in Python-driven workflows.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no known vulnerabilities, low install friction, and a permissive license. Install it if you need to use SQLAlchemy with Databricks. Be aware that LargeBinary, PickleType, Enum types, and CHECK constraints are not yet supported—verify these don't block your schema design before committing.
Install
databricks-sqlalchemy on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Actively maintained as of July 2026 with recent releases. Depends on three runtime packages: databricks_sql_connector, pyarrow, and sqlalchemy.
Requires Databricks workspace with Unity Catalog enabled and valid API token; hive_metastore catalog support is untested.
License in practice
Apache-2.0 permissive license allows use in commercial and open-source projects with minimal restrictions; attribution required.
Quickstart
pip install databricks-sqlalchemy
from sqlalchemy import create_engine
engine = create_engine(
"databricks://token:dapi***@host.cloud.databricks.com"
"?http_path=/sql/1.0/warehouses/***&catalog=main&schema=default"
)Verify before relying
- Whether LargeBinary and PickleType limitations are blocking for your use case (documented as unsupported).
- Whether CHECK constraint and Enum type support roadmap aligns with your schema design needs.
- Compatibility with Databricks SQL connector versions beyond what the package pins.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <4.0.0,>=3.8.0 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesdatabricks_sql_connectorpyarrowsqlalchemy |
| Maintenance | Actively maintained 43 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 37,744,755 / month, #721 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9 |
Evidence: databricks_sqlalchemy-2.0.10-py3-none-any.whl
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See also databricks-labs-remorph · duckdb-engine · iomete-sqlalchemy · snowflake-sqlalchemy · sqlalchemy-databricks · sqlalchemy-trino · databricks-dbapi · databricks-labs-lsql · sqlalchemy-hana · teradatasqlalchemy