google-cloud-bigquery-storage

Google Cloud Bigquery Storage API client library

google-cloud-bigquery-storage Permissive license Apache-2.0 Active ★ 5,370 v2.40.0 released 2026-08-06

Install

google-cloud-bigquery-storage on PyPI

pip

pip install google-cloud-bigquery-storage

uv

uv add google-cloud-bigquery-storage

poetry

poetry add google-cloud-bigquery-storage

Package facts

License	Apache-2.0 (permissive)
Python support	supports the current Python release (>=3.10)
Install friction	low — pure-Python wheel
Runtime dependencies	5 — google-api-core, google-auth, grpcio, proto-plus, protobuf
Maintenance	actively maintained — 7 days since the last release
Last repo commit	2026-08-13
First released	2018-11-30
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: google_cloud_bigquery_storage-2.40.0-py3-none-any.whl

Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software 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 :: Internet

About google-cloud-bigquery-storage

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

Python Client for BigQuery Storage

BigQuery Storage_:

Client Library Documentation_
Product Documentation_

.. |stable| image:: https://img.shields.io/badge/support-stable-gold.svg :target: https://github.com/googleapis/google-cloud-python/blob/main/README.rst#stability-levels .. |pypi| image:: https://img.shields.io/pypi/v/google-cloud-bigquery-storage.svg :target: https://pypi.org/project/google-cloud-bigquery-storage/ .. |versions| image:: https://img.shields.io/pypi/pyversions/google-cloud-bigquery-storage.svg :target: https://pypi.org/project/google-cloud-bigquery-storage/ .. _BigQuery Storage: https://cloud.google.com/bigquery/ .. _Client Library Documentation: https://cloud.google.com/python/docs/reference/bigquerystorage/latest/summary_overview .. _Product Documentation: https://cloud.google.com/bigquery/

Quick Start

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

Select or create a Cloud Platform project._
Enable billing for your project._
Enable the BigQuery Storage._
Set up Authentication._

.. _Select or create a...

Read as markdown · JSON record · Source repository · Homepage

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

This package provides a Python client library for Google Cloud BigQuery Storage, enabling efficient read and write access to BigQuery datasets through a dedicated storage API.

Installation is straightforward with low friction—the package is a pure Python wheel with five well-maintained Google Cloud dependencies (google-api-core, google-auth, grpcio, proto-plus, protobuf). The project is actively maintained with a release just 7 days old and shows strong community adoption (5370 GitHub stars).

Licensed under Apache-2.0 (permissive), this package imposes no significant restrictions on use, modification, or distribution in most contexts.

Usage

pip install google-cloud-bigquery-storage

from google.cloud import bigquery_storage_v1

client = bigquery_storage_v1.BigQueryStorageClient()

Requires Python >= 3.10; Google Cloud Platform credentials must be configured (via application default credentials, service account key, or environment variable) before client instantiation.

Verdict: A production-ready, actively maintained client library for BigQuery Storage with low install friction and no known vulnerabilities. The Apache-2.0 license is permissive, and the package supports current Python versions (3.10–3.14). Suitable for projects requiring efficient bulk data access to BigQuery.

Needs verification

Whether the package requires additional system libraries or compiled dependencies beyond its Python dependencies.
Specific performance characteristics or throughput limits when used with large-scale data transfers.

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