gcloud-aio-bigquery
Python Client for Google Cloud BigQuery
Decision gist · record as of 2026-08-14
Yes, if you need async BigQuery access in a concurrent application. The package has low install friction, active maintenance, no known vulnerabilities, and a permissive license. It is well-positioned in the top 1000 PyPI packages by download volume. Install it only if your application is already async-first; synchronous workloads should use the official google-cloud-bigquery library instead.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.8 or later; authentication credentials must be available via gcloud-aio-auth (typically through Application Default Credentials or explicit credential configuration).
- Low friction installation with a single runtime dependency (gcloud-aio-auth).
- Active maintenance as of 2026-08-13 with 348 repository stars and stable production status.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions; you may use, modify, and distribute this package freely provided you include the license notice.
last release 2024-02-16 (910 days) · last repo commit 2026-08-13 · 348 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 27,232,853 downloads/mo, #864 on PyPI
Alternatives
Verify before relying
pip install gcloud-aio-bigquery
from gcloud.aio.bigquery import BigQueryClient
import asyncio
async def query():
async with BigQueryClient() as client:
result = await client.query(project_id='my-project', query='SELECT 1')
return result- Whether the package supports streaming inserts or only query operations
- Performance characteristics and concurrency limits compared to the synchronous REST variant
- Specific BigQuery API version coverage and feature parity with the official google-cloud-bigquery library
What it is and what it does
This package is an asyncio-compatible Python client for Google Cloud BigQuery that wraps the BigQuery API with non-blocking I/O. It shares a codebase with gcloud-rest-bigquery and depends on gcloud-aio-auth for credential handling. The package is designed for applications that need to query BigQuery datasets without blocking the event loop, making it suitable for concurrent workloads and async frameworks.
The client operates on Python 3.8 through 3.12 and is maintained as production-stable. It abstracts away the complexity of async HTTP calls to BigQuery, allowing developers to write concurrent code that scales better under load than traditional synchronous clients. The single runtime dependency keeps the installation lightweight.
Use it for
- Run multiple BigQuery queries concurrently in an async web service without blocking request handlers.
- Integrate BigQuery data operations into async ETL pipelines or background job processors.
- Query BigQuery from async Python frameworks (FastAPI, aiohttp, asyncio-based services) without thread pools.
- Build data analytics dashboards that fetch BigQuery results asynchronously while handling other requests.
- Perform exploratory data analysis in Jupyter notebooks with async/await syntax for cleaner code flow.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need async BigQuery access in a concurrent application.
The package has low install friction, active maintenance, no known vulnerabilities, and a permissive license. It is well-positioned in the top 1000 PyPI packages by download volume. Install it only if your application is already async-first; synchronous workloads should use the official google-cloud-bigquery library instead.
Install
gcloud-aio-bigquery on PyPI
Before you install
Low friction installation with a single runtime dependency (gcloud-aio-auth). Active maintenance as of 2026-08-13 with 348 repository stars and stable production status.
Requires Python 3.8 or later; authentication credentials must be available via gcloud-aio-auth (typically through Application Default Credentials or explicit credential configuration).
License in practice
MIT license permits commercial and private use with minimal restrictions; you may use, modify, and distribute this package freely provided you include the license notice.
Quickstart
pip install gcloud-aio-bigquery
from gcloud.aio.bigquery import BigQueryClient
import asyncio
async def query():
async with BigQueryClient() as client:
result = await client.query(project_id='my-project', query='SELECT 1')
return resultVerify before relying
- Whether the package supports streaming inserts or only query operations
- Performance characteristics and concurrency limits compared to the synchronous REST variant
- Specific BigQuery API version coverage and feature parity with the official google-cloud-bigquery library
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.8,<4.0 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagegcloud-aio-auth |
| Maintenance | Actively maintained 910 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 27,232,853 / month, #864 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/StableIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Internet |
Evidence: gcloud_aio_bigquery-7.1.0-py3-none-any.whl
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See also gcloud-rest-bigquery · gcloud-aio-storage · gcloud-aio-datastore · gcloud-rest-datastore · gcloud-aio-pubsub · gcloud-aio-taskqueue · gcloud-rest-taskqueue · gcloud-aio-auth · bigquery · caio