head to head · open source
ClickHouse vs bigquery-utils
ClickHouse has 49,959 GitHub stars, 8,971 forks, 7,547 open issues and last shipped yesterday. bigquery-utils has 1,312 stars, 337 forks, 64 open issues and last shipped 3 months ago. ClickHouse leads on adoption by 3,708% (49,959 vs 1,312 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 | ★ 50K | ★ 1.3K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | C++ | Jupyter Notebook |
| Last push | 2026-09-18 | 2026-07-03 |
| Forks | ⑂ 9.0K | ⑂ 337 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick ClickHouse if
- You weight community size — 50K 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 written in C++ that delivers real time analytical query performance on massive datasets. It operates within the broader data infrastructure ecosystem, serving as a high performance alternative to traditional row oriented databases for OLAP workloads.
read the full ClickHouse overview →
About bigquery-utils
Useful scripts, UDFs, views, notebooks, dashboards, and other utilities for migrating to and operating a data warehouse in Google BigQuery, aimed at data engineers, analytics engineers, and migration teams working on Google Cloud Platform.
read the full bigquery-utils overview →
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Frequently asked questions
Is ClickHouse or bigquery-utils more popular?
ClickHouse has 49,959 GitHub stars and bigquery-utils has 1,312. 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 (49,959 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.