sqlalchemy-bigquery

SQLAlchemy dialect for BigQuery

sqlalchemy-bigquery Permissive license Active ★ 5,370 v1.17.2 released 2026-08-06

Install

sqlalchemy-bigquery on PyPI

pip

pip install sqlalchemy-bigquery

uv

uv add sqlalchemy-bigquery

poetry

poetry add sqlalchemy-bigquery

Package facts

License	not declared (permissive)
Python support	supports the current Python release (>=3.10)
Install friction	low — pure-Python wheel
Runtime dependencies	5 — google-api-core, google-auth, google-cloud-bigquery, packaging, sqlalchemy
Maintenance	actively maintained — 7 days since the last release
Last repo commit	2026-08-13
First released	2015-03-30
Popularity	one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13)
Known vulnerabilities	none known (OSV.dev, checked 2026-08-13)

Evidence: sqlalchemy_bigquery-1.17.2-py3-none-any.whl

Keywords: bigquery, sqlalchemy

Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Database :: Front-Ends

About sqlalchemy-bigquery

from the package's own PyPI description — quoted content, verbatim

SQLAlchemy Dialect for BigQuery

SQLALchemy Dialects_

Dialect Documentation_
Product Documentation_

.. |GA| image:: https://img.shields.io/badge/support-GA-gold.svg :target: https://github.com/googleapis/google-cloud-python/blob/main/README.rst#general-availability .. |pypi| image:: https://img.shields.io/pypi/v/sqlalchemy-bigquery.svg :target: https://pypi.org/project/sqlalchemy-bigquery/ .. |versions| image:: https://img.shields.io/pypi/pyversions/sqlalchemy-bigquery.svg :target: https://pypi.org/project/sqlalchemy-bigquery/ .. _SQLAlchemy Dialects: https://docs.sqlalchemy.org/en/14/dialects/ .. _Dialect Documentation: https://googleapis.dev/python/sqlalchemy-bigquery/latest .. _Product Documentation: https://cloud.google.com/bigquery/docs/

Quick Start

In order to use this library, you first need to go through the following steps:

Select or create a Cloud Platform project._
[Optional] Enable billing for your project._
Enable the BigQuery Storage API._
Setup Authentication._

.. _Select or create a Cloud Platform project.: https://console.cloud.google.com/project .....

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AI interpretation — verify before relying

AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page

SQLAlchemy dialect that enables you to use BigQuery as a database backend through SQLAlchemy's ORM and query interface, supporting standard SQL operations on BigQuery datasets and tables.

Low friction installation with a pure-wheel distribution and five runtime dependencies (google-api-core, google-auth, google-cloud-bigquery, packaging, sqlalchemy). Actively maintained with a release 7 days ago and 5370 repository stars.

Permissive license treatment allows commercial and private use without restriction, making it suitable for both open-source and proprietary projects.

Usage

pip install sqlalchemy-bigquery

from sqlalchemy import create_engine, Table, MetaData, select, func
engine = create_engine('bigquery://project')
table = Table('dataset.table', MetaData(bind=engine), autoload=True)
result = engine.execute(select([func.count('*')], from_obj=table)).scalar()

Requires Python >= 3.10 and Google Cloud authentication setup (service account credentials or Application Default Credentials). BigQuery Storage API must be enabled in your GCP project.

Verdict: Production-ready dialect (Development Status 5) with active maintenance, no known vulnerabilities, and low install friction. Suitable for projects needing SQLAlchemy integration with BigQuery, though authentication and GCP project setup are prerequisites.

Needs verification

Whether the optional bqstorage extras provide measurable performance gains for typical large-dataset workloads
Compatibility matrix with specific SQLAlchemy versions beyond the general runtime dependency

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