Laravel vs Django 2025 Guide

Laravel and Django remain the leading backend frameworks in 2025. Both have evolved significantly with AI integration, real-time features, and modern tooling. At ZIRA Software, we use both frameworks based on project requirements.

2025 Framework Overview

Laravel 11                      Django 5.x
├── PHP 8.2+                    ├── Python 3.10+
├── Reverb (WebSockets)         ├── Channels (WebSockets)
├── Octane (High Performance)   ├── ASGI (Async Support)
├── Eloquent ORM                ├── Django ORM
├── Blade Templates             ├── Django Templates
└── First-party AI packages     └── Rich AI/ML ecosystem

Performance Comparison

Benchmark: 10,000 requests, JSON API response

Laravel + Octane (Swoole)
├── Requests/sec: 5,200
├── Avg latency: 8ms
├── Memory: 180MB
└── CPU: 45%

Django + Gunicorn + uvicorn
├── Requests/sec: 3,800
├── Avg latency: 12ms
├── Memory: 220MB
└── CPU: 52%

Winner: Laravel (with Octane)
Note: Both are production-ready for most use cases

Real-Time Capabilities

// Laravel Reverb - Native WebSockets
class MessageSent implements ShouldBroadcast
{
    public function broadcastOn(): array
    {
        return [new PrivateChannel('chat.' . $this->chatId)];
    }
}

// Self-hosted, horizontally scalable
// No external service costs

# Django Channels
class ChatConsumer(AsyncWebsocketConsumer):
    async def connect(self):
        await self.channel_layer.group_add(
            self.room_name,
            self.channel_name
        )
        await self.accept()

    async def receive(self, text_data):
        await self.channel_layer.group_send(
            self.room_name,
            {'type': 'chat_message', 'message': text_data}
        )

Verdict: Laravel Reverb provides simpler setup; Django Channels offers more flexibility.

AI/ML Integration

// Laravel - OpenAI integration
use OpenAI\Laravel\Facades\OpenAI;

$response = OpenAI::chat()->create([
    'model' => 'gpt-4-turbo',
    'messages' => [['role' => 'user', 'content' => $prompt]],
]);

// Embeddings with pgvector
$results = Document::orderByRaw(
    'embedding <-> ?::vector', [$queryEmbedding]
)->limit(10)->get();

# Django - Native Python AI ecosystem
from openai import OpenAI
import numpy as np
from pgvector.django import VectorField

client = OpenAI()
response = client.chat.completions.create(
    model="gpt-4-turbo",
    messages=[{"role": "user", "content": prompt}]
)

# Direct access to PyTorch, TensorFlow, scikit-learn
import torch
model = torch.load('custom_model.pt')

Verdict: Django wins for ML/AI-heavy applications due to Python ecosystem.

Developer Experience

| Feature | Laravel | Django | |---------|---------|--------| | Learning Curve | Gentle | Moderate | | Documentation | Excellent | Excellent | | CLI Tools | Artisan (extensive) | manage.py (good) | | Admin Panel | Filament/Nova | Built-in | | Code Style | Pint | Black/Ruff | | Testing | PHPUnit/Pest | pytest/unittest |

Ecosystem 2025

Laravel:

• Reverb (WebSockets)
• Pulse (Monitoring)
• Pennant (Feature Flags)
• Folio (File-based routing)
• Octane (Performance)
• Cashier (Payments)

Django:

• Channels (WebSockets)
• Django Ninja (Fast APIs)
• Celery (Task queues)
• Django REST Framework
• Wagtail (CMS)
• django-allauth (Auth)

When to Choose Laravel

✓ PHP team expertise
✓ Rapid application development
✓ E-commerce platforms
✓ SaaS applications
✓ Real-time features (Reverb)
✓ Monolithic architecture preference

When to Choose Django

✓ Python team expertise
✓ AI/ML integration required
✓ Data science applications
✓ Scientific computing
✓ Content-heavy sites
✓ Admin-heavy applications

Code Comparison: REST API

// Laravel
class PostController extends Controller
{
    public function index()
    {
        return PostResource::collection(
            Post::with('author')->paginate(20)
        );
    }

    public function store(StorePostRequest $request)
    {
        $post = $request->user()->posts()->create(
            $request->validated()
        );
        return new PostResource($post);
    }
}

# Django REST Framework
class PostViewSet(viewsets.ModelViewSet):
    queryset = Post.objects.select_related('author')
    serializer_class = PostSerializer
    permission_classes = [IsAuthenticatedOrReadOnly]
    pagination_class = StandardPagination

    def perform_create(self, serializer):
        serializer.save(author=self.request.user)

Conclusion

Both frameworks excel in 2025. Laravel leads in developer experience and real-time features. Django dominates AI/ML integration and data-heavy applications. Choose based on team expertise and project requirements.

Need framework guidance? Contact ZIRA Software for architecture consultation.