head to head · open source
seaweedfs vs bigquery-utils
seaweedfs has 35,871 GitHub stars, 3,099 forks, 772 open issues and last shipped yesterday. bigquery-utils has 1,314 stars, 336 forks, 64 open issues and last shipped 4 months ago. seaweedfs leads on adoption by 2,630% (35,871 vs 1,314 stars). seaweedfs is written in Go under Apache-2.0; bigquery-utils is written in Jupyter Notebook under Apache-2.0. seaweedfs has attracted 9% as many forks as stars, bigquery-utils 26%. seaweedfs 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
| seaweedfs | bigquery-utils | |
|---|---|---|
| GitHub stars | ★ 36K | ★ 1.3K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Go | Jupyter Notebook |
| Last push | 2026-11-02 | 2026-07-03 |
| Forks | ⑂ 3.1K | ⑂ 336 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick seaweedfs if
- You weight community size — 36K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Go
- 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 seaweedfs
SeaweedFS SeaweedFS is a simple and highly scalable distributed file system. There are two objectives: 1. to store billions of files! 2. to serve the files fast! One weed binary serves an S3 object store, a POSIX file system, and a lakehouse with S3 Tables, all over the same data. Each blob is one disk read away, capacity grows by starting another volume server, and cloud storage can be cached or tiered transparently. Both read and write operations have O(1) complexity and can run at the full speed supported by the underlying hardware. Download Binaries for different platforms Wiki Documentation Community…
read the full seaweedfs 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 seaweedfs or bigquery-utils more popular?
seaweedfs has 35,871 GitHub stars and bigquery-utils has 1,314. seaweedfs has the larger community by that measure.
Are seaweedfs and bigquery-utils free?
Both are open source. seaweedfs is licensed under Apache-2.0 and bigquery-utils under Apache-2.0. Neither carries a licence fee.
What is the difference between seaweedfs and bigquery-utils?
seaweedfs is written in Go 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, seaweedfs or bigquery-utils?
Choose seaweedfs if you want the larger community (35,871 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.