Laravel relies heavily on organized data handling. From arrays to queues and collections, Laravel uses different data structures under the hood. Here’s a clear breakdown for better understanding and real-world usage.
📦 Arrays
Step 1: Arrays are used everywhere — in route files, config files, view parameters, and more.
Step 2: Laravel treats arrays like building blocks for defining structure, e.g.:
['name' => 'WebNestix', 'type' => 'blog']
Step 3: Arrays are passed to views:
return view('home', ['user' => $user]);
🌀 Collections
Step 1: Collections are advanced wrappers around arrays, offering fluent method chaining.
Step 2: Create with:
$collection = collect([1, 2, 3]);
Step 3: Useful methods include
map(),
filter(),
pluck(),
sum(),
groupBy(), etc.
Step 4: Collections are returned automatically from Eloquent queries:
$users = User::where('status', 'active')->get();
⏳ Queues
Step 1: Laravel supports queues for handling background tasks like emails or exports.
Step 2: A queue behaves like a data structure (FIFO — first in, first out).
Step 3: Dispatch jobs with:
dispatch(new SendWelcomeEmail($user));
Step 4: Queues can be backed by database, Redis, or SQS.
📚 Stack and Pipeline
Step 1: Middleware in Laravel runs through a stack (LIFO) structure.
Step 2: Laravel also has a Pipeline class for sending data through a chain of transformations.
Step 3: Example pipeline syntax:
Pipeline::send($data)->through([...])->thenReturn();
🧭 Caching & Config as Data
Step 1: Laravel config files are structured arrays.
Step 2: Laravel cache drivers (Redis, file, DB) use underlying storage formats like key-value pairs (map structure).
Step 3: You can store arrays or collections directly in cache:
Cache::put('users', $users, now()->addMinutes(10));
🧠 Summary
- Arrays = native structure for configs, params, view data
- Collections = powerful wrapper for array processing
- Queues = async FIFO task handler
- Stack/Pipeline = sequential logic processing
- Cache = key-value storage structure
Understanding Laravel's internal data structures improves both performance and code readability.