A backend system demonstrating cache-first architecture using FastAPI, Redis, and PostgreSQL.
This project shows how modern backend services improve performance by retrieving data from a cache before querying the database.
• Redis-based caching • Database fallback • Cache expiration • Faster API responses • Clean backend architecture
Python FastAPI Redis PostgreSQL SQLAlchemy Uvicorn
Client ↓ FastAPI API ↓ Redis Cache ↓ PostgreSQL Database
Flow:
Request received ↓ Check Redis cache ↓ If cached → return data ↓ If not cached → query database ↓ Store result in Redis ↓ Return response
│ ├── app │ ├── main.py │ ├── database.py │ ├── models.py │ ├── cache.py │ ├── cache_service.py │ └── routes.py │ ├── requirements.txt └── README.md
Install dependencies
pip install -r requirements.txt
Start Redis
redis-server
Run API
uvicorn app.main:app --reload --port 8004
Open documentation
GET /products/1
First response:
source: database
Second response:
source: cache
• Distributed caching • Cache invalidation strategies • API monitoring • Cache analytics
Push to GitHub
Run inside the project folder:
git init git add . git commit -m "API Cache System with Redis and PostgreSQL" git branch -M main git remote add origin https://github.com/rohitahari/api-cache-system.git git push -u origin main
Your Backend Portfolio Now
You now have 5 serious backend systems:
URL Shortener Job Queue System API Rate Limiter Auth Service API Cache System
These represent the core backend infrastructure patterns.
That means:
project-building phase → complete
If you want, the next thing I can show you is extremely important for the next stage:
the exact roadmap from these 5 projects → first $1000 online as a backend developer.