Arrays and linked lists both store an ordered sequence of elements, which makes it tempting to think of them as interchangeable. They're not — the way each one lays out data in memory produces very different performance characteristics, and picking the wrong one for a given workload can quietly make your code much slower than it needs to be.

This post lines the two up side by side across the operations that actually matter in practice, so you have a concrete rule of thumb instead of a vague "it depends."

Head-to-Head Comparison

Assuming n is the number of elements:

Operation                  Array        Linked List
------------------------------------------------------
Access by index             O(1)         O(n)
Search (unsorted)           O(n)         O(n)
Insert at the end           O(1)*        O(1) (with tail pointer)
Insert at the front         O(n)         O(1)
Insert in the middle        O(n)         O(n) to find + O(1) to link
Delete from the front       O(n)         O(1)
Memory layout                contiguous   scattered, linked by pointers
Extra memory per element     none         one (or two) pointers

* O(1) amortized for a dynamic array (like Python's list); a true
  fixed-size array can't grow at all once full.

Why Array Access Is O(1) but Linked List Access Isn't

An array stores its elements in one contiguous block of memory, so the address of element i can be computed directly with simple arithmetic: base_address + i * element_size. No traversal needed — that's what makes arr[i] O(1).

A linked list has no such shortcut. Each node only knows the address of the next node, so reaching index i means starting at the head and following i pointers one at a time — O(n) in the worst case.

Why Linked List Insertion at the Front Is O(1) but Array Insertion Isn't

Inserting at the front of an array means every existing element has to shift one position to the right to make room — O(n) work, every time:

arr = [10, 20, 30]
arr.insert(0, 5)   # every element shifts right
print(arr)

Output:

[5, 10, 20, 30]

A linked list just needs to create a new node and point it at the old head — nothing else in the list has to move, so it's O(1) regardless of how many elements it already holds.

The Practical Rule of Thumb

Reach for an array when you mostly read by index and rarely insert/remove from the front or middle — it's also far more cache-friendly, since contiguous memory plays nicely with how CPUs prefetch data. Reach for a linked list when you frequently insert or remove from the front (or know the node already, e.g. implementing a stack or queue) and random access by index isn't something you need often. In practice, most general-purpose code defaults to a dynamic array (Python's list, Java's ArrayList) — linked lists earn their place specifically when front-insertion speed matters.