head to head · open source
ClickHouse vs bigquery-utils
ClickHouse has 50,719 GitHub stars, 9,204 forks, 7,547 open issues and last shipped yesterday. bigquery-utils has 1,314 stars, 336 forks, 64 open issues and last shipped 4 months ago. ClickHouse leads on adoption by 3,760% (50,719 vs 1,314 stars). ClickHouse is written in C++ under Apache-2.0; bigquery-utils is written in Jupyter Notebook under Apache-2.0. ClickHouse has attracted 18% as many forks as stars, bigquery-utils 26%. ClickHouse was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| ClickHouse | bigquery-utils | |
|---|---|---|
| GitHub stars | ★ 51K | ★ 1.3K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | C++ | Jupyter Notebook |
| Last push | 2026-11-02 | 2026-07-03 |
| Forks | ⑂ 9.2K | ⑂ 336 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick ClickHouse if
- You weight community size — 51K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches C++
- You value the larger contributor base for long-term maintenance
pick bigquery-utils if
- You want the bigquery-utils feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Jupyter Notebook
- You evaluated both and bigquery-utils fits your workflow better
About ClickHouse
ClickHouse® is an open source column oriented database management system that allows generating analytical data reports in real time. How To Install (Linux, macOS, FreeBSD) Useful Links Official website has a quick high level overview of ClickHouse on the main page. ClickHouse Cloud ClickHouse as a service, built by the creators and maintainers. Tutorial shows how to set up and query a small ClickHouse cluster. Documentation provides more in depth information. YouTube channel has a lot of content about ClickHouse in video format. ClickHouse Theater contains presentations and videos about ClickHouse. Slack and…
read the full ClickHouse overview →
About bigquery-utils
BigQuery Utils BigQuery is a serverless, highly scalable, and cost effective cloud data warehouse with an in memory BI Engine and machine learning built in. This repository provides useful utilities to assist you in migration and usage of BigQuery. Getting Started This repository is broken up into: Dashboards Pre built dashboards for common use cases System Tables Looker Studio Dashboards built on BigQuery's INFORMATION SCHEMA metadata views to understand organization's slot and reservation utilization, job execution, and job errors. Notebooks Colab notebooks for various BigQuery related use cases. BigQuery…
read the full bigquery-utils overview →
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Frequently asked questions
Is ClickHouse or bigquery-utils more popular?
ClickHouse has 50,719 GitHub stars and bigquery-utils has 1,314. ClickHouse has the larger community by that measure.
Are ClickHouse and bigquery-utils free?
Both are open source. ClickHouse is licensed under Apache-2.0 and bigquery-utils under Apache-2.0. Neither carries a licence fee.
What is the difference between ClickHouse and bigquery-utils?
ClickHouse is written in C++ and bigquery-utils in Jupyter Notebook. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, ClickHouse or bigquery-utils?
Choose ClickHouse if you want the larger community (50,719 stars) or its Apache-2.0 licence terms. Choose bigquery-utils if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.