head to head · open source
dlt vs bigquery-utils
dlt has 5,872 GitHub stars, 606 forks, 434 open issues and last shipped 2 days ago. bigquery-utils has 1,312 stars, 337 forks, 64 open issues and last shipped 3 months ago. dlt leads on adoption by 348% (5,872 vs 1,312 stars). dlt is written in Python under Apache-2.0; bigquery-utils is written in Jupyter Notebook under Apache-2.0. dlt has attracted 10% as many forks as stars, bigquery-utils 26%. dlt was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (data-warehouse), so they are genuine substitutes rather than adjacent tools.
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
| dlt | bigquery-utils | |
|---|---|---|
| GitHub stars | ★ 5.9K | ★ 1.3K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Jupyter Notebook |
| Last push | 2026-09-18 | 2026-07-03 |
| Forks | ⑂ 606 | ⑂ 337 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick dlt if
- You weight community size — 5.9K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Python
- 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 dlt
dlt (data load tool) is an open source Python library, licensed under Apache 2.0, that automates tedious data loading by moving data from messy, often unstructured sources into well structured, typed datasets, and it is built for Python developers and data engineers who want to load data without adopting a platform.
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 dlt or bigquery-utils more popular?
dlt has 5,872 GitHub stars and bigquery-utils has 1,312. dlt has the larger community by that measure.
Are dlt and bigquery-utils free?
Both are open source. dlt is licensed under Apache-2.0 and bigquery-utils under Apache-2.0. Neither carries a licence fee.
What is the difference between dlt and bigquery-utils?
dlt is written in Python 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, dlt or bigquery-utils?
Choose dlt if you want the larger community (5,872 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.