Data Structures in Swift: A Practical Guide for iOS Developers

Every Swift developer eventually runs into the same moment.

The app works fine… until it doesn't.

Scrolling becomes sluggish. Memory usage slowly creeps up. A feature that worked perfectly in testing starts behaving strangely in production. And when you dig deep enough, the issue often traces back to one thing: how data is stored and managed.

That's where swift data structures come in.

This blog is a practical walkthrough of data structures in Swift, not from a textbook point of view, but from how they actually show up in real iOS apps. If you've ever wondered how DSA in Swift connects to everyday development, this guide is for you.

Why Data Structures Matter in Swift Apps

Every app is built around data.

User profiles, feeds, messages, settings, caches - everything lives somewhere in memory.

Choosing the right data structure affects:

• App performance
• Memory consumption
• Code clarity
• Stability under real-world usage

This is why data structures and algorithms in Swift aren't just interview topics. They quietly decide whether your app feels smooth or frustrating.

Data Structures Available in Swift

Let's walk through the most important data structures available in Swift and where they fit best.

Arrays

Arrays are the most commonly used data structure in Swift. They store elements in an ordered collection.

// Creating an array of names
var users = ["Antony", "Alice", "Bob", "Charlie"]
// Creating an array of integers
var numbers = [1, 2, 3, 4, 5]

// Accessing elements
let firstElement = numbers[0]

// Modifying elements
numbers.append(6)
numbers[2] = 10

// Iterating through an array
for number in numbers {
    print(number)
}

Use Cases:

• Displaying lists in tables or collections
• Maintaining order (feeds, steps, timelines)
• Sequential access

Arrays are fast for reading values by index, but inserting or removing items often can be expensive. If you're frequently modifying large arrays, performance can degrade faster than expected.

Dictionaries

Dictionaries store data as key-value pairs, optimized for quick lookups.

// Creating a dictionary
var userAges = ["Olive": 25, "Jennifer": 30, "Jake": 27]

// Accessing values
let oliveAge = userAges["Olive"]

// Modifying values
userAges["David"] = 35

// Iterating through a dictionary
for (user, age) in userAges {
    print("\(user): \(age)")
}

Common Use Cases:

• Caching API responses
• Storing user preferences
• Mapping IDs to objects

If you ever find yourself looping through an array just to find a single item by ID, a dictionary is almost always the better choice.

Sets

Sets store unique, unordered values.

// Creating a set of integers
var uniqueNumbers: Set<Int> = [1, 2, 3, 3, 4, 5]

// Adding and removing elements
uniqueNumbers.insert(5)
uniqueNumbers.remove(2)

// Checking membership
let containsSeven = uniqueNumbers.contains(7)

Why Sets are Useful:

• Preventing duplicates
• Fast membership checks
• Cleaner logic when order doesn't matter

They're perfect for cases like tracking visited items, enabled features, or selected filters.

Stacks

Stacks follow a Last In, First Out (LIFO) pattern.

Swift doesn't provide a built-in stack type, but arrays are commonly used to implement one.

// Creating a stack
var stack: [Int] = []

// Pushing elements onto the stack
stack.append(1)
stack.append(2)
stack.append(3)

// Popping elements
let poppedElement = stack.popLast()

Real-world Uses:

• Navigation history
• Undo / redo actions
• Temporary state management

Stacks feel simple, but they show up more often than you might realize.

Queues

Queues work on a First In, First Out (FIFO) principle.

// Creating a queue
var queue: [Int] = []

// Enqueuing elements
queue.append(1)
queue.append(2)
queue.append(3)

// Dequeuing elements
let dequeuedElement = queue.removeFirst()

Where queues appear:

• Task scheduling
• Event handling
• Background processing

Queues help maintain order when timing matters—especially when handling async operations.

Linked Lists

A linked list is made up of individual nodes, and each node stores some data along with a reference to another node. Instead of elements sitting next to each other in memory (like arrays), each node simply "points" to the next one. Depending on how those links are structured, linked lists can be singly linked, doubly linked, or even circular, each serving different use cases.

// Node structure for a singly linked list
class Node<S> {
    var value: S
    var next: Node?
    
    init(_ value: S) {
        self.value = value
    }
}

// Creating a singly linked list
let node1 = Node(1)
let node2 = Node(2)
let node3 = Node(3)

node1.next = node2
node2.next = node3

Why linked lists exist:

• Efficient insertions and deletions
• No need to shift elements in memory

However, they come with trade-offs. Accessing elements is slower, and Swift developers often prefer arrays unless linked-list behavior is truly needed.

Trees (Binary Trees)

Trees organize data hierarchically. Binary trees, in particular, allow each node to have two children.

// Node structure for a binary tree
class BinaryTreeNode<T> {
    var value: T
    var left: BinaryTreeNode?
    var right: BinaryTreeNode?
    
    init(_ value: T) {
        self.value = value
    }
}

// Creating a binary tree
let root = BinaryTreeNode(1)
root.left = BinaryTreeNode(2)
root.right = BinaryTreeNode(3)

Practical examples:

• Folder structures
• Parsing expressions
• Decision trees

While Swift doesn't ship with a built-in tree structure, understanding them is essential for advanced DSA in Swift and complex app logic.

Graphs

Graphs are data structures built from nodes (also called vertices) and the connections between them, known as edges. These connections can be one-way (directed) or two-way (undirected). Depending on the problem you're solving, graphs can be represented in different ways—most commonly using adjacency lists for flexibility and efficiency, or adjacency matrices for quick lookups.

// Implementing an adjacency list for a graph
class Graph {
    var adjacencyList: [Int: [Int]] = [:]
    
    func addEdge(from source: Int, to destination: Int) {
        if adjacencyList[source] == nil {
            adjacencyList[source] = []
        }
        adjacencyList[source]?.append(destination)
    }
}

// Creating a graph
let graph = Graph()
graph.addEdge(from: 1, to: 2)
graph.addEdge(from: 1, to: 3)
graph.addEdge(from: 2, to: 4)

Where graphs are useful:

• Navigation systems
• Social connections
• Dependency resolution

Graphs are powerful but complex. They're rarely used directly in small apps, but they form the backbone of many large-scale systems.

Choosing the Right Data Structure

There's no universal "best" data structure.

The right one depends on:

• Whether order matters
• How often data changes
• Lookup speed requirements
• Memory constraints

This is where understanding data structures in Swift turns into real engineering judgment.

Performance, Stability, and Real Users

Poor data structure choices don't always cause immediate crashes. More often, they lead to:

• Gradual memory growth
• Slower screens
• Edge-case failures under load

These issues usually surface only after real users start using the app at scale.

Final Thoughts

Learning swift data structures isn't about memorizing definitions. It's about knowing how data behaves inside your app and choosing the right tool for the job.

When you understand data structures and algorithms in Swift, you write code that's:

• Easier to maintain
• Faster in production
• More resilient under pressure

And that's exactly what modern iOS apps need.