Learn how Giselle and n8n differ in their key features, development activity, technology stack and community adoption, so you can decide which of these low-code/no-code platforms is best for you.
Last 30 days
Last commit
16 hours agoRepository age
2 yearsVersion
v0.75.6License
Apache-2.0Repository
giselles-ai/giselle
Last 30 days
Last commit
11 hours agoRepository age
7 yearsVersion
2.44.6Self-hosted
YesRepository
n8n-io/n8n
n8n appears to have several advantages over Giselle, particularly in popularity, growth, maturity and features. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
n8n significantly outpaces Giselle in community adoption with 208,343 stars compared to 559 stars on GitHub. This 372.7x difference suggests n8n has a much larger and more active community. In terms of developer contributions, n8n has 61,218 forks, indicating strong developer engagement.
n8n is growing faster, adding 2,640 stars in the last 30 days (+1.3%) against adding 3 stars for Giselle (+0.5%). n8n is both larger and pulling further ahead.
Both projects show recent activity, with Giselle last updated 16 hours ago and n8n 11 hours ago.
Both tools share common technology foundations, being built with JavaScript, CSS, Bash, Typescript. However, they differ in their additional technology choices: Giselle uses JSX, Next.js while n8n leverages SCSS, Vue.
n8n has been in development longer, starting 7 years ago, compared to Giselle which began 2 years ago. This 5.2-year head start suggests n8n may have more mature features and established processes.
Giselle is licensed under Apache-2.0, while n8n's license terms are not publicly specified.
Both tools serve similar use cases in Low-Code/No-Code. However, they also have distinct specializations: Giselle also focuses on AI Agent Platforms while n8n extends into Workflow Automation.
n8n provides self-hosting options for complete data control and customization, while Giselle may be primarily cloud-based or require different deployment approaches.