head to head · open source

rustfs vs bigquery-utils

rustfs has 33,108 GitHub stars, 1,482 forks, 28 open issues and last shipped yesterday. bigquery-utils has 1,312 stars, 337 forks, 64 open issues and last shipped 3 months ago. rustfs leads on adoption by 2,423% (33,108 vs 1,312 stars). rustfs is written in Rust under Apache-2.0; bigquery-utils is written in Jupyter Notebook under Apache-2.0. rustfs has attracted 4% as many forks as stars, bigquery-utils 26%. rustfs 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.

rustfs ★ 33K bigquery-utils ★ 1.3K category Data & Analytics

← all 15422 open source comparisons

Side by side

rustfs bigquery-utils
GitHub stars ★ 33K ★ 1.3K
License Apache-2.0 Apache-2.0
Written in Rust Jupyter Notebook
Last push 2026-09-18 2026-07-03
Forks ⑂ 1.5K ⑂ 337
Self-hosting Yes Yes
Data ownership Your server Your server

pick rustfs if

  • You weight community size — 33K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Rust
  • You value the larger contributor base for long-term maintenance

full rustfs profile →

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

full bigquery-utils profile →

About rustfs

RustFS is an open source, S3 compatible, high performance distributed object storage system written in Rust, aimed at teams running data lakes, AI, and big data workloads who want MinIO style operational simplicity without the restrictions of an AGPL licence.

read the full rustfs 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 →

More in Data & Analytics

Mermaid ★ 90K Crawl4AI ★ 84K Scrapling ★ 82K Apache Superset ★ 75K echarts ★ 67K scrapy ★ 64K

Related comparisons

mermaid vs clickhouse crawl4ai vs clickhouse scrapling vs clickhouse apache-superset vs clickhouse mermaid vs apache-pinot clickhouse vs duckdb crawl4ai vs apache-pinot scrapling vs apache-pinot firecrawl vs scrapy firecrawl vs crawlee browser-use vs crawl4ai crawl4ai vs scrapling crawl4ai vs scrapy scrapling vs scrapy crawl4ai vs easyspider scrapling vs easyspider godot vs pixijs mermaid vs apache-superset supabase vs metabase mermaid vs echarts grafana vs apache-superset apache-superset vs echarts mermaid vs metabase mermaid vs pixijs

More Data Warehousing & Processing projects

Compare either of these against the rest of the Data Warehousing & Processing field.

rustfs vs ClickHouse rustfs vs seaweedfs rustfs vs parse-server rustfs vs Apache Pinot rustfs vs dlt rustfs vs hue rustfs vs arc

Frequently asked questions

Is rustfs or bigquery-utils more popular?

rustfs has 33,108 GitHub stars and bigquery-utils has 1,312. rustfs has the larger community by that measure.

Are rustfs and bigquery-utils free?

Both are open source. rustfs is licensed under Apache-2.0 and bigquery-utils under Apache-2.0. Neither carries a licence fee.

What is the difference between rustfs and bigquery-utils?

rustfs is written in Rust 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, rustfs or bigquery-utils?

Choose rustfs if you want the larger community (33,108 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.