Learn how **Azimutt ** and Mathesar differ in their key features, development activity, technology stack and community adoption, so you can decide which of these database tools & guis is best for you.
Last 30 days
Last commit
2 months agoRepository age
5 yearsLicense
MITRepository
azimuttapp/azimutt
Last 30 days

Mathesar appears to have several advantages over **Azimutt **, particularly in popularity, activity and features. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Mathesar leads in popularity with 5,159 stars vs 2,194 stars for **Azimutt **. The 135% higher star count indicates stronger community adoption. In terms of developer contributions, Mathesar has 488 forks, indicating moderate developer engagement.
**Azimutt ** and Mathesar are moving at much the same rate, adding 8 stars and adding 25 stars respectively over the last 30 days (+0.4% vs +0.5%). Neither is pulling away from the other on momentum alone.
Mathesar shows more recent development activity with its last commit 1 day ago, while **Azimutt ** was last updated 2 months ago. This suggests Mathesar is being more actively maintained.
Both tools share common technology foundations, being built with JavaScript, CSS, Typescript. However, they differ in their additional technology choices: **Azimutt ** uses JSX, Elixir while Mathesar leverages Bash, Python, SCSS.
Both projects started around the same time, with **Azimutt ** beginning 5 years ago and Mathesar 6 years ago.
**Azimutt ** uses the MIT license, which is more permissive than Mathesar's GPL-3.0 license, potentially offering greater flexibility for commercial use and integration.
Both tools serve similar use cases in Database Tools & GUIs. However, they also have distinct specializations: **Azimutt ** also focuses on Data Visualization while Mathesar extends into Low-Code/No-Code.
Mathesar provides self-hosting options for complete data control and customization, while **Azimutt ** may be primarily cloud-based or require different deployment approaches.