When we talk about habit trackers, most people imagine a simple checklist.
But turning that into a real, scalable full-stack app is a perfect playground for performance, data modeling, and clear architecture.
Over the next 20 days, I'm sharing every step of building a Habit Tracker with:
- Next.js for the frontend (fast, SEO-friendly React framework)
- Fastify for a high-performance Node.js API
- MongoDB + Mongoose for flexible, schema-driven storage
This post documents Stage 1 - Planning & Data Design, the foundation that sets the tone for the whole project.
Defining the MVP
My goal is a lean first release that's still valuable:
- Create & edit habits - simple CRUD with validation
- Daily logging - mark each habit as done/not-done per day
- Weekly & monthly summaries - quick analytics for motivation
Staying focused here keeps scope tight and shipping fast.
Choosing the Stack
- Next.js: server-side rendering and API routes for snappy UX
- Fastify: modern, lightweight, and faster than Express
- MongoDB/Mongoose: flexible schema with room for growth
I debated Express vs. Fastify for a while; Fastify's plugin ecosystem and performance won.
Data Modeling
Three main collections emerged:
- User: auth info and settings
- Habit: name, description, schedule
- DailyLog: user-habit-date relationship + status
Indexes were planned early for quick weekly/monthly queries.
Lessons Learned
- Plan indexes first: analytics speed depends on it.
- Keep MVP honest: say "no" to nice-to-have features until the core is proven.
Open Source & Collaboration
The entire codebase and documentation are public:
👉 GitHub Repo
I'll push updates daily as I tackle UI, API endpoints, testing, and deployment.
Pull requests, issues, or architectural discussions are welcome.
Let's Connect
I'm sharing daily reflections, code snippets, and behind-the-scenes challenges on LinkedIn.
If you'd like to follow the journey, swap ideas, or collaborate on similar projects, join me there:
👉 [linkedin.com/in/ariansj(https://www.linkedin.com/in/ariansj/)
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