How to Build an App Like JustEat: A Full-Stack Developer’s Guide to Clone App Development

Food delivery app like JustEat have transformed how people order food — fast, flexible, and right at your doorstep. With the surge in demand for hyperlocal delivery platforms, launching your own JustEat-like app has never been more relevant. Whether you’re an agency, a startup founder, or a solo entrepreneur, chances are you’ve considered building a JustEat clone. I’ve done exactly that — built it from the ground up — and in this guide, I’ll walk you through every critical piece.

This isn’t fluff. I’ll break down how I approached it in both JavaScript (Node.js + React) and PHP (Laravel), the rationale behind my choices, and the gritty details that only someone who’s actually built one can give. You’ll see how database schemas were structured, how payments and third-party APIs were integrated, and what trade-offs come with each tech stack.

By the end, you’ll understand both the architecture and developer mindset needed to build an app like JustEat — and know when it makes more sense to build custom or go with a ready-made solution like the Justeat Clone from Miracuves.

Choosing the Right Tech Stack: JavaScript (Node.js + React) vs PHP (Laravel or CodeIgniter)

When I started building the JustEat clone, the first big decision was the tech stack. The right choice depends on your goals — speed of development, scalability, your team’s skillset, and future plans. I built the app in both JavaScript and PHP stacks to understand their nuances and offer flexibility to different clients.

JavaScript Stack (Node.js + React)
For the JS-based build, I went with Node.js for the backend and React for the frontend. Node.js offered non-blocking I/O, which made handling concurrent requests during peak hours (think Friday night dinner rush) much smoother. I used Express.js as the server framework because it’s lightweight and fits naturally into a microservices-oriented backend structure. On the frontend, React gave me component reusability and fast rendering via the virtual DOM. It also simplified implementing dynamic filters, cart updates, and real-time order tracking. I chose MongoDB as the database here because of its flexible, nested JSON structure — perfect for storing menus, restaurant profiles, and dynamic delivery zones.

PHP Stack (Laravel or CodeIgniter)
For the PHP version, I went with Laravel for most builds due to its elegant syntax, built-in tools, and active ecosystem. CodeIgniter is faster for lightweight applications but lacks the architectural advantages of Laravel. Laravel’s Eloquent ORM made it easier to model relationships — customers, orders, restaurants, delivery partners — and to keep data integrity tight. For the frontend, I used Blade (Laravel’s templating engine) which was ideal for rendering server-side views. MySQL was the natural database here — structured, reliable, and battle-tested for transactional apps like food delivery.

When to Choose What
If your app is meant to be highly dynamic, scale aggressively, and involve real-time features like order tracking, go with JavaScript (Node.js + React). If you’re building a robust, well-documented backend with predictable user flows, Laravel in PHP offers great speed, security, and support. For founders with tighter budgets and faster launch goals, PHP is usually quicker to implement with minimal dependencies. But if you’re aiming to raise funding and scale quickly, JS gives you more flexibility and modern frontend edge.

Read More : Best JustEat Clone Scripts in 2025: Features & Pricing Compared

Database Design: Structuring for Flexibility and Scale

One of the first things I had to think through was the data model — because if that’s wrong, everything else becomes harder. For a JustEat-style app, you’re essentially managing restaurants, customers, menus, orders, and delivery logistics. The design needed to support flexibility (like multi-restaurant ordering), scalability (thousands of concurrent users), and extensibility (add-ons like loyalty programs later).

JavaScript Stack (MongoDB)
In the Node.js version, I used MongoDB for its document-based schema, which played really well with dynamic data structures. Here’s how a sample restaurant document looked:

{
  "name": "Pizza Palace",
  "slug": "pizza-palace",
  "location": {
    "lat": 12.934,
    "lng": 77.610
  },
  "menu": [
    {
      "name": "Margherita",
      "price": 6.99,
      "tags": ["vegetarian"],
      "customizations": [
        { "name": "Extra Cheese", "price": 1.5 }
      ]
    }
  ],
  "delivery_zones": [
    { "zipcode": "560001", "min_order": 10 }
  ]
}

It let me nest menus and customizations within the restaurant document — which made reads super fast on the frontend when displaying a full restaurant view. For user data, I had collections like users, orders, restaurants, and delivery_partners — each indexed for fast access and joined in code via lookup pipelines when needed.

PHP Stack (MySQL)
For the Laravel version, I built a normalized schema using Eloquent relationships. Each table had its clear purpose — users, restaurants, dishes, order_items, orders, and delivery_addresses. I avoided deeply nested JSON structures here because relational databases shine with structured joins. Here’s a simplified schema layout:

• users: id, name, email, phone
• restaurants: id, name, address_id, status
• dishes: id, restaurant_id, name, price, category_id
• orders: id, user_id, restaurant_id, total_price, status
• order_items: id, order_id, dish_id, quantity, price

To handle dynamic customizations (like extra cheese or spice level), I created a customizations table and linked it via pivot tables. It’s a bit more verbose than MongoDB, but Laravel’s ORM made it manageable and safer for enforcing constraints.

Scalability Considerations
In both stacks, I used indexing strategies — like on restaurant_id, zipcode, and status — to keep query performance tight. Caching was another layer (covered later), but structurally, both designs were tuned for read-heavy access, especially during lunch/dinner rush windows. I also accounted for future scale by supporting soft deletes and multi-tenancy (important if the founder wants to launch in multiple cities).

Key Modules and Features: Building the Core Experience of an App Like JustEat

Once the database was solid, I moved on to building the core modules that make or break a JustEat-style food delivery platform. These included the restaurant listing and search filters, cart and order flow, delivery status tracking, admin management, and analytics. Each had to be modular, scalable, and intuitive for both users and admins.

1. Restaurant Discovery and Filters
In the JavaScript stack (React frontend), I created a component-based structure where each filter — cuisine, rating, delivery time, location — was its own functional unit. I used React Context for global state like selected filters and Redux to manage async search requests via Axios. The Node.js backend exposed endpoints like:

GET /api/restaurants?cuisine=italian&delivery_time=30

This queried MongoDB with $match and $limit operations for pagination.
In Laravel, I used query scopes and Eloquent relationships. Filters were applied via controller logic, often using chained queries:

$restaurants = Restaurant::whereHas('cuisines', fn($q) => $q->where('name', $request->cuisine))
  ->where('delivery_time', '<=', $request->delivery_time)
  ->paginate(20);

2. Cart and Checkout
React handled the cart state locally with context. On checkout, I pushed the entire cart object to the backend using:

POST /api/orders

The backend validated restaurant IDs, calculated final price (including delivery fee), and stored the order atomically.
In Laravel, I handled cart logic server-side using session storage and stored orders in the orders and order_items tables, with validation middleware checking user auth, cart integrity, and restaurant status.

3. Order Tracking and Delivery Flow
Using Socket.IO in Node.js, I enabled real-time status updates: “Order Placed → Cooking → Out for Delivery → Delivered.” Delivery partners had their own dashboard, and the backend emitted order status updates via WebSockets.
In the PHP version, I went with AJAX polling (every 15 seconds) to fetch current order status. It’s less real-time but good enough for MVPs, especially on shared hosting or limited budget projects.

4. Admin Panel
For the JS stack, I built a separate React-based admin panel with protected routes using JWT authentication. Admins could manage restaurants, approve menu updates, and monitor active orders.
In Laravel, I used Blade with Laravel Breeze for quick scaffolding. RBAC (Role-Based Access Control) was implemented via Laravel Gates and Policies, giving fine-grained permission control.

5. Ratings and Reviews
Both stacks included a review module. On React/Node.js, reviews were stored directly in the reviews collection and indexed by restaurant ID. On Laravel/MySQL, I normalized this into a reviews table with user_id, restaurant_id, rating, and comment.

Data Handling: Third-Party APIs vs Manual Restaurant Listings

When it came to getting restaurant data into the platform, I had to support two models: (1) using third-party APIs to pull in data, and (2) allowing restaurants or admins to manually manage listings. Both needed to coexist because some clients preferred API-driven onboarding while others wanted full manual control.

Using Third-Party APIs
In the JavaScript stack, I integrated APIs like Zomato (when still public), FourSquare Places, and custom B2B restaurant data providers. For example, to pull listings from a mock API, I’d use Axios in Node.js:

const axios = require('axios');
const fetchRestaurants = async (location) => {
  const response = await axios.get(`https://api.partner.com/restaurants?lat=${location.lat}&lng=${location.lng}`);
  return response.data;
};

I cleaned and normalized the data before inserting into MongoDB, ensuring structure consistency (menus, coordinates, contact info). I used a cron job with node-cron to sync data every 6 hours.

In Laravel, I used Guzzle to fetch and handle external APIs. I wrapped it inside artisan commands so an admin could trigger a fetch on demand:

$response = Http::get('https://api.partner.com/restaurants', ['lat' => $lat, 'lng' => $lng]);
$data = $response->json();

I validated and saved data using Eloquent models. I also used Laravel Scheduler (app/Console/Kernel.php) to automate sync jobs.

Manual Listing via Admin Panel
For manually curated apps, I built admin modules where restaurant owners or platform managers could upload menus, set delivery zones, and manage availability.

In React (JS stack), I created a form-driven interface with validation and upload logic using React Hook Form. Data was pushed via:

POST /api/restaurants

In Laravel, the Blade-powered admin panel had dynamic input fields using Alpine.js for form flexibility. Uploads went through Laravel’s file storage and validation layers.

Image Handling
On both stacks, I used AWS S3 for image uploads. In Node.js, I used multer-s3. In Laravel, the Storage::disk('s3') method worked seamlessly.

Key Consideration
Always sanitize and normalize data from third-party sources. I also added moderation queues in the admin for imported data — nothing went live until approved.

Read More :  Reasons startup choose our justeat clone over custom development

API Integration: Structuring Endpoints for Reliability and Performance

A robust API layer is what ties your frontend and backend together — and in a JustEat-style platform, it has to support everything from guest browsing to secure payments and real-time updates. I structured the API layer to be modular, secure, and future-ready in both Node.js and PHP (Laravel).

JavaScript (Node.js + Express) API Structure
I followed REST principles for clarity and scalability. Here’s how my core routes looked:

• GET /api/restaurants – List restaurants based on filters
• GET /api/restaurants/:id – Single restaurant with menu
• POST /api/orders – Place an order
• GET /api/orders/:id – Track an order
• POST /api/reviews – Submit a review
• POST /api/auth/login – User login
• POST /api/auth/register – New user signup
• POST /api/payment/checkout – Stripe or Razorpay checkout intent

I used Express middlewares for validation (express-validator), rate limiting (express-rate-limit), and JWT authentication (jsonwebtoken). For real-time features like delivery status updates, I used Socket.IO with an order-status namespace.

PHP (Laravel) API Design
Laravel’s API routing (routes/api.php) let me define clean, versioned endpoints:

Route::prefix('v1')->group(function () {
  Route::get('/restaurants', [RestaurantController::class, 'index']);
  Route::get('/restaurants/{id}', [RestaurantController::class, 'show']);
  Route::post('/orders', [OrderController::class, 'store']);
  Route::get('/orders/{id}', [OrderController::class, 'show']);
  Route::post('/reviews', [ReviewController::class, 'store']);
  Route::post('/auth/login', [AuthController::class, 'login']);
});

I used Laravel Passport for OAuth and token-based authentication, though Sanctum works well for lighter apps. Validation was handled via FormRequest classes, keeping the controllers clean.

Rate Limiting & Security
In Node.js, I set up rate limits on login and checkout routes to prevent abuse. In Laravel, I leveraged middleware like throttle:60,1 and verified to guard sensitive endpoints. CSRF protection was automatically handled in Laravel Blade-based forms.

Documentation & Testing
For both stacks, I used Swagger (via swagger-jsdoc in Node, l5-swagger in Laravel) to generate API docs for the frontend team and external partners. This saved us tons of back-and-forth.

Frontend and UI Structure: React vs Blade — Designing for Speed and UX

Frontend development for a food delivery app like JustEat is all about responsiveness, clarity, and speed. Users want to search, explore, order, and pay — all without friction. I built two versions: one using React (for Node.js backend) and the other using Laravel Blade (for PHP backend). Both delivered the same core UX but were approached very differently under the hood.

React Frontend (Node.js Stack)
I broke the UI into modular, reusable components: Header, RestaurantCard, MenuItem, CartDrawer, CheckoutPage, OrderTracking, and Footer. React Router was used for page navigation, and I used React Context for managing global states like cart data and user session. For responsiveness, I relied on Tailwind CSS and Flexbox/Grid utilities to make it mobile-first. I also added skeleton loaders and shimmer effects for slow networks using libraries like react-loading-skeleton.

Routing was handled like this:

<Route path="/" element={<HomePage />} />
<Route path="/restaurant/:slug" element={<RestaurantDetail />} />
<Route path="/checkout" element={<Checkout />} />

Dynamic UI behaviors like cart updates, quantity changes, and modals were handled using local state or Redux where needed. I also added lazy loading for images and route-level code splitting using React.lazy() and Suspense to reduce initial load time.

Blade Frontend (Laravel Stack)
For the PHP version, I stuck to Laravel’s Blade templating system. While server-rendered, Blade gave me full control over structure and logic. I used @include and @component to manage reusable chunks like navbar, restaurant-list, and menu-item.

Pages were structured like:

@extends('layouts.app')

@section('content')
  @include('partials.restaurant_list', ['restaurants' => $restaurants])
@endsection

CSS was handled with Bootstrap for quicker prototyping and clean mobile responsiveness. Interactivity (like cart updates and filtering) was handled with a mix of Alpine.js and jQuery for lighter weight and simpler state updates.

UX Considerations
Across both stacks, I designed for quick restaurant discovery, fast cart access, and a frictionless checkout. Key UX features included:

• Sticky cart preview on mobile
• Persistent login state via JWT (React) or sessions (Blade)
• Real-time feedback on order progress (Socket.IO for JS, polling for PHP)
• One-click re-order feature in the user profile

The end goal was to reduce user clicks and make the whole journey — from browsing to checkout — seamless on both desktop and mobile.

Authentication & Payments: Securing Access and Enabling Seamless Checkout

Security and frictionless payments are non-negotiable in a JustEat-style app. Whether it’s a user logging in, a restaurant accessing their dashboard, or a delivery partner updating status — authentication had to be airtight. And once the cart was ready, the payment process needed to feel smooth, fast, and trustworthy. I implemented both using robust libraries in JavaScript and PHP.

Authentication in Node.js + React
I used JWT (JSON Web Tokens) for authentication. On user login or registration, the backend (Node.js + Express) generated a signed token using jsonwebtoken, which was stored in HTTP-only cookies for security.

const token = jwt.sign({ userId: user._id }, process.env.JWT_SECRET, { expiresIn: '7d' });
res.cookie('token', token, { httpOnly: true });

React used axios to include credentials on each request. For protected routes (like /checkout, /my-orders), I built a PrivateRoute component that checked for the token and redirected if missing.

Authentication in Laravel
I used Laravel’s built-in Auth scaffolding for traditional session-based login, and Laravel Sanctum for API token authentication (great for mobile apps or SPAs). Middleware like auth:sanctum ensured only authenticated users could place orders or view dashboards.

Login looked like this:

$user = User::where('email', $request->email)->first();
if (Hash::check($request->password, $user->password)) {
  return $user->createToken('auth_token')->plainTextToken;
}

Tokens were stored client-side and sent via headers on each API request.

Payment Integration: Stripe & Razorpay
In the Node.js app, I used Stripe with the official SDK. On the frontend, I used @stripe/react-stripe-js for handling card input via Elements, and on the backend, I created a payment intent:

const paymentIntent = await stripe.paymentIntents.create({
  amount: totalAmount * 100,
  currency: 'usd',
  metadata: { orderId: newOrder._id }
});

On the PHP side (Laravel), I integrated Razorpay for Indian clients. I created orders server-side using Razorpay’s SDK:

$order = $api->order->create([
  'receipt' => 'ORD123',
  'amount' => $total * 100,
  'currency' => 'INR'
]);

Frontend handled the checkout using Razorpay’s JS library. On success, the payment ID was sent back to the backend for order confirmation and storage.

Security Measures
I enforced role-based access control (RBAC) in both stacks — restaurant owners couldn’t access admin dashboards, and delivery partners had access only to assigned orders. I also implemented brute-force protection using express-rate-limit in Node and throttle middleware in Laravel.

Testing & Deployment: CI/CD, Docker, and Production Readiness

Once the core features were solid, it was time to get serious about stability and delivery. Testing and deployment are where many clone projects stumble, so I made sure both the JavaScript and PHP versions were production-ready, testable, and easy to maintain across environments.

JavaScript (Node.js + React) Testing & Deployment

For testing, I wrote unit tests using Jest and Supertest for API endpoints:

const request = require('supertest');
const app = require('../app');

describe('GET /api/restaurants', () => {
  it('should return a list of restaurants', async () => {
    const res = await request(app).get('/api/restaurants');
    expect(res.statusCode).toEqual(200);
    expect(res.body).toHaveProperty('data');
  });
});

On the frontend (React), I used React Testing Library for component behavior and cypress for end-to-end testing. I automated testing via GitHub Actions, with steps to lint, test, and deploy only if all checks passed.

For deployment, I used Docker to containerize both the frontend and backend:

# Node.js Dockerfile
FROM node:18
WORKDIR /app
COPY package*.json ./
RUN npm install
COPY . .
EXPOSE 5000
CMD ["node", "server.js"]

I ran both services using Docker Compose, with separate containers for MongoDB, Node, and NGINX as a reverse proxy. In production, I used PM2 to manage Node processes and ensure auto-restarts on crashes.

PHP (Laravel) Testing & Deployment

Laravel comes with PHPUnit baked in. I wrote feature tests for order placement, user login, and admin operations:

public function testUserCanPlaceOrder()
{
  $user = User::factory()->create();
  $response = $this->actingAs($user)->post('/api/orders', [
    'restaurant_id' => 1,
    'items' => [...]
  ]);
  $response->assertStatus(201);
}

I also tested form validation, auth middleware, and order status updates. Laravel’s test database made isolation easy.

For deployment, I used Apache on an Ubuntu VPS with mod_php and PHP-FPM. Laravel apps were served via virtual hosts. I used Envoyer for zero-downtime deploys and Laravel Forge to manage the infrastructure, SSL, and cron jobs.

To containerize Laravel, I used Sail or my own Dockerfile with php:8.1-fpm, nginx, and mysql. For queue handling (emails, order notifications), I used Supervisor on the server or Laravel Horizon for Redis-backed jobs.

CI/CD Pipeline

Both stacks followed the same pipeline logic:

• Git push to main
• Run tests and lint checks
• Build Docker image
• Push to container registry
• Deploy to production with env-specific configs

For Node.js, I used GitHub Actions + Docker Hub + DigitalOcean.
For Laravel, I used GitHub Actions + Forge + Linode or AWS Lightsail.

Pro Tips: Real-World Lessons, Performance Hacks, and UX Wins

After launching multiple versions of this JustEat-style platform for different clients, I’ve run into my fair share of edge cases, bottlenecks, and quick wins. These are the things I wish I’d implemented earlier — the practical improvements that make your clone app smoother, faster, and easier to scale.

1. Caching Where It Matters
Database reads can add up fast — especially on the restaurant listing and menu endpoints. In the Node.js version, I integrated Redis and used it to cache frequently accessed routes like /api/restaurants, setting a TTL of 10 minutes. I used node-cache for smaller use-cases like delivery fee calculation.

In Laravel, I used the built-in Cache facade and tagged caching for menus per restaurant:

Cache::tags(['menus', 'restaurant_' . $id])->remember('menu_' . $id, 600, function () {
  return Menu::where('restaurant_id', $id)->get();
});

2. Optimize Images Early
Serving uncompressed images will kill your mobile load times. I used Cloudinary in both stacks to auto-optimize and resize images on the fly. On upload, images were resized into multiple breakpoints and served via CDN. This alone dropped page load times by 40% on mobile.

3. Mobile UX: Sticky Cart and Speed Taps
Most users order via mobile. So I added a sticky cart preview at the bottom of the screen (React and Blade), always showing item count and total. I also increased the size of clickable targets (like “Add to Cart” or “Checkout”) using extra padding — made a huge difference for thumbs.

4. Use WebSockets Selectively
For real-time order updates, WebSockets are tempting but heavy if not managed right. I limited Socket.IO usage to only the OrderTrackingPage and shut the connection as soon as the order reached “Delivered.” For Laravel, I used Laravel Echo + Pusher only on premium plans — polling was good enough for MVPs.

5. Monitor Like a Hawk
I integrated Sentry for error logging and LogRocket for user session tracking in the React app. In Laravel, I used Laravel Telescope during staging and moved to Bugsnag for production alerts. You can’t fix what you can’t see — these tools helped catch weird bugs before users even noticed.

6. Avoid Over-Engineering Early
At first, I spent time making the cart logic support 5 edge cases (combo meals, coupons, loyalty points). Turns out most users just want to pick food, pay, and eat. Keep it simple for V1 — you can always add complexity once people are actually using it.

Read More : Key JustEat Features for Food Delivery Apps

Final Thoughts: Build Smart or Launch Fast?

Building a JustEat-style food delivery platform from scratch taught me two things: first, it’s absolutely doable with the right tech stack and modular thinking. Second, you need to be ruthless about scope and trade-offs — because real-world use always diverges from the clean ideal in your mind.

When to Go Custom
If you’re a tech-savvy founder with a solid dev team and a unique twist — maybe a regional market with hyperlocal features, or an AI-driven recommendation system — custom is the way to go. You’ll need flexibility and fine control over UX, APIs, and infrastructure. The Node.js + React stack gave me unmatched agility for this, especially when working with real-time data and modern frontend patterns.

When to Choose PHP
Laravel worked beautifully when the client needed fast development, reliable performance, and admin-heavy workflows. It’s perfect for a founder who wants a working MVP in weeks, not months. The tooling, ORM, and community make Laravel hard to beat for startup teams building solid delivery platforms on a budget.

When to Go Ready-Made
There’s absolutely no shame in skipping the dev cycle entirely. If your goal is to launch quickly, validate demand, or start onboarding restaurants in under 30 days — going with a tested, pre-built solution like the Justeat Clone from Miracuves makes perfect sense. You get everything I talked about — APIs, admin panels, mobile-ready UI — but without the build stress. You can always customize or scale from there once you’ve got traction.

FAQs: JustEat Clone Development – Founder Questions Answered

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