Unpacking the no-code AI titans whose 260K+ GitHub stars
Author
Omar Alva
Senior DevSecOps Engineer
July 8, 2025
Hello automation enthusiasts! π Ready to dive into the exciting world of no-code and low-code AI tools? Today we're exploring three absolute powerhouses that are revolutionizing how we build AI-powered workflows and applications. Whether you're a developer looking to speed up your process or a complete beginner wanting to harness AI without writing a single line of code, this guide has got you covered!
What does the community say ?
Let's start with the numbers that matter β GitHub stars are like the popularity contest of the open-source world, and they tell us a lot about community adoption and trust.
The Updated Results Are In:
π₯ 1st Place: N8N - Leading the pack with 115,000 stars
π₯ 2nd Place: Dify - Strong runner-up with 106,000 stars
π₯ 3rd Place: Flowise - Impressive showing with 41,000 stars
N8N now holds the clear lead in this competitive space, having recently reached the 115K milestone
Dify continues to show strong growth with over 106K stars, while Flowise maintains solid community support with 41K stars.All three platforms have experienced significant growth, demonstrating the increasing demand for no-code and low-code AI automation solutions.
The gap between N8N and Dify has widened recently, with N8N pulling ahead by approximately 9,000 stars. Meanwhile, Flowise has shown substantial growth, adding over 10,000 stars since earlier measurements that showed it at around 30K stars. This puts all three tools in an excellent position within the GitHub ecosystem, with N8N and Dify ranking among the top projects globally.
N8N (pronounced "en-eight-en" or "nodemation") is like the Swiss Army knife of workflow automation. Created in 2019 by Jan Oberhauser in Berlin, this bad boy has grown into something truly special.
What Makes N8N Special:
Fair-code licensed β giving you the best of both open-source and commercial worlds
400+ integrations out of the box
Visual programming with the flexibility to drop into JavaScript or Python when needed
Self-hosting freedom β your data, your rules
Perfect For: Teams that need maximum flexibility and aren't afraid of a bit of complexity. If you want to connect literally everything to everything else, N8N is your friend.
Dify is the new kid on the block that's making serious waves in the AI development space. Think of it as your AI application development platform that actually makes sense.
What Makes Dify Shine:
LLM-first design β built specifically for large language model applications
Retrieval-Augmented Generation (RAG) engine for smarter AI responses
Model-agnostic β works with GPT, Claude, Llama, and tons more
Visual workflow builder that even non-techies can master
Perfect For: Anyone wanting to build AI-powered applications without getting lost in technical complexity. If ChatGPT and workflow automation had a baby, it would be Dify13.
Flowise is your go-to platform for building custom LLM applications with a drag-and-drop interface3. It's built on LangChain, which means you get all the power of that ecosystem in a visual package14.
What Makes Flowise Awesome:
LangChain integration β leverage the entire LangChain ecosystem visually
Multi-agent systems for complex AI workflows
Document Q&A capabilities β chat with your PDFs and documents
Template library for quick starts
Perfect For: Developers and teams focused specifically on LLM applications who want rapid prototyping capabilities.
Pros and Cons: The Real Talk
N8N: The Good, The Bad, and The Powerful
β Pros:
Incredible flexibility β if it has an API, N8N can probably connect to it
Open-source freedom β self-host for free with complete control
Extensive customization β custom nodes, JavaScript functions, you name it
Strong community β 100K+ developers means lots of help and templates
Cost-effective at scale β especially compared to per-task pricing models
β Cons:
Steep learning curve β not exactly beginner-friendly
Self-hosting complexity β requires technical know-how for setup and maintenance
Limited official support β community-driven help can be hit or miss
Documentation gaps β sometimes you're left figuring things out yourself
β
Dify: The AI-First Approach
β Pros:
User-friendly interface β actually designed for humans
Comprehensive LLM support β works with virtually any mode
Built-in RAG capabilities β no need to build knowledge retrieval from scratch
Rapid prototyping β from idea to working app in minutes
Visual workflow design β see your AI logic in action
β Cons:
AI-focused limitations β not great for general workflow automation
Variable size limits in cloud version can be restrictive
Newer platform β smaller community and fewer resources
Support quality can be inconsistent, especially on paid plans
β
Flowise: The LLM Specialist
β Pros:
LLM-optimized β purpose-built for language model applications
Easy prototyping β drag, drop, and you're building AI apps
LangChain integration β access to a massive ecosystem of tools
Multi-modal support β text, images, and more
Active development β frequent updates and new features
β Cons:
Limited scope β only really useful for LLM applications
Hosting constraints β fewer deployment options than competitors
Smaller community β compared to N8N and Dify
Learning curve β despite being "no-code," it still requires understanding of LLM concepts
Installation: Getting Your Hands Dirty with Docker
Let's get these tools running on your machine! All three support Docker Compose, making installation pretty straightforward.
Access Dify at http://localhost for setup and then normal use.
β
Installing Flowise with Docker Compose
# Clone the repository
git clone https://github.com/FlowiseAI/Flowise.gitcd Flowise/docker
# Copy environment file
cp .env.example .env
# Start the container
docker compose up -d
Access Flowise at http://localhost:3000.
β
The Ultimate Comparison Table
Final Thoughts: Which Tool Should You Choose?
Here's the honest truth β there's no "one size fits all" answer, but here's my take:
Choose N8N if:
You need maximum flexibility and aren't afraid of complexity
You're building workflows that go beyond just AI
You want complete control over your automation environment
You have the technical chops to handle self-hosting
Choose Dify if:
You're focused on building AI applications
You want something user-friendly that gets you results fast
You need comprehensive LLM support out of the box
You're new to AI development but want professional results
Choose Flowise if:
You're specifically building LLM-powered applications
You want to leverage the LangChain ecosystem
You need rapid prototyping capabilities
You're comfortable with a more specialized tool
β
Ready to Get Started?
The world of no-code AI tools is absolutely exploding right now, and these three platforms are leading the charge. Whether you're a solo developer, part of a startup, or working in a large enterprise, there's never been a better time to start automating and building AI-powered solutions.
My recommendation? Start with the free versions of all three! Spin them up with Docker, play around for a weekend, and see which one clicks with your brain and your use case. The learning investment you make now will pay dividends as AI becomes even more central to how we work.
What's your experience with these tools? Drop a comment below and let the community know what you're building, what challenges you've faced, and what awesome automations you've created. The best way to learn is from each other, and I'd love to hear your stories!
Ready to automate your world? Pick your tool and let's get building! π
