Array vs List Comparison - Choosing the Right Sequence Type in C#

Vaibhav • September 10, 2025

Arrays and List<string> are the two most common ways to store sequences of data in C#. While they look similar and can often be used interchangeably, they have important differences in performance, flexibility, and usage. In this article, we’ll compare arrays and lists across key dimensions: initialization, resizing, access, iteration, memory, and best practices. We’ll reference concepts from previous articles (like initialization and iteration) but won’t re-explain them in detail.

What is an array?

An array is a fixed-size, strongly-typed sequence. Once created, its length cannot change. Arrays are fast and memory-efficient for known-size data.

string[] names = { "Ada", "Linus", "Grace" };
names[2] = "Alan"; // direct access

• Best for: Known-size, numeric or simple data, fast indexed access.
• Limitations: Size is fixed; adding/removing requires creating a new array.

What is a List<string>?

List<string> is a resizable, strongly-typed sequence. You can add, remove, and insert elements dynamically. Internally, it uses an array and resizes as needed.

var names = new List<string> { "Ada", "Linus", "Grace" };
names.Add("Alan"); // grows automatically
names.RemoveAt(1); // removes "Linus"

• Best for: Dynamic lists, frequent additions/removals, indexed access.
• Limitations: Slightly more memory overhead than arrays; insert/remove in the middle is slower for large lists.

Initialization and resizing

Arrays

int[] arr = new int[5]; // length fixed at 5

You cannot add or remove elements. To "resize," you must create a new array and copy values.

Lists

var list = new List<int>();
list.Add(1);
list.Add(2);
// grows as needed

Lists automatically resize their internal array when capacity is exceeded.

Access and iteration

• Arrays: Fast indexed access (arr[i]), foreach for read-only iteration.
• Lists: Fast indexed access (list[i]), foreach for iteration, plus methods like Add, Remove, Insert.

// Array iteration
foreach (int x in arr)
{
    Console.WriteLine(x);
}

// List iteration
foreach (int y in list)
{
    Console.WriteLine(y);
}

Memory and performance

• Arrays: Slightly more memory-efficient; no overhead for resizing or extra methods.
• Lists: Use a backing array and may allocate more memory than needed to avoid frequent resizing.

When to use arrays

• Data size is fixed and known in advance.
• Maximum performance and minimal memory usage are required.
• Interfacing with APIs or libraries that require arrays.
• Simple numeric or primitive data.

When to use lists

• Data size is unknown or changes over time.
• You need to add, remove, or insert elements dynamically.
• Convenience methods like Add, Remove, Contains are useful.
• Working with collections in modern C# code.

Common mistakes and pitfalls

• Trying to add/remove from an array - Not possible; use a list instead.
• Using a list for fixed-size, performance-critical data - Prefer arrays for maximum speed and minimal memory.
• Forgetting to set initial capacity for large lists - Can cause repeated resizing and slowdowns.
• Assuming lists are always faster - For small or fixed-size data, arrays are simpler and faster.

Practical example: copying between arrays and lists

// Convert array to list
int[] arr = { 1, 2, 3 };
var list = new List<int>(arr);

// Convert list to array
int[] arr2 = list.ToArray();

You can easily convert between arrays and lists using constructors and methods like ToArray().

Checklist: array vs list

• Fixed-size, maximum speed: Array
• Dynamic size, convenience: List<string> or List<int>
• Need to add/remove elements: List<string> or List<int>
• Interfacing with APIs: Use what the API requires
• Numeric or primitive data: Array
• Complex objects, changing data: List<string> or List<int>

Summary

Arrays and lists are both essential tools for storing sequences in C#. Use arrays for fixed-size, high-performance scenarios and lists for dynamic, flexible collections. Arrays are slightly faster and more memory-efficient, but lists offer powerful methods and automatic resizing. Choose based on your data’s needs, and don’t be afraid to convert between them as your program evolves.