When it comes to managing and organizing data properly then stack and queue data structures are considered to be most important that every programmer or developer should know. Their structure might confuse beginners in the starting because they allow to follow operation on either one or both ends. They both follows different principles as stack uses LIFO that stands for Last In First Out whereas queue uses FIFO that stands for First In First Out.
In this blog we will talking about the basics of stack and queue data structures along with their key differences to understand both the terms properly.
What is Stack Data Structure?
Stack is a linear data structure which follows the Last In First Out (LIFO) order to arrange elements. Stack data structure opens from only one end so there is only one possible manner to pop (delete an element) and push (add an element) onto the stack .
In the stack data structure there are different blocks that help you to understand the representation of the stack.
In this pictorial representation above, we are adding element ‘ C ‘ in the stack and a pointer ‘TOP’ pointing to the topmost block of the stack where we need to push an element. Here element ‘ C ‘ added last in the stack.
In stack there are few terminologies that are required to understand the concept of stack in data structure properly :
- TOP : TOP is a pointer in the stack data structure. This pointer in stack points the topmost block of the stack in data structure. If the stack is having the condition of underflow then the value of the TOP is -1 (when stack is empty).
- PUSH (Adding element in the stack) : Push is an operation in the stack , we will add elements in a stack using push( ) operation.
- POP (Remove an element from the stack) : We will remove an element from the stack using the pop ( ) operation.
What is Queue Data Structure?
Queue data structure is a fundamental concept of managing and storing data in the data structure (linear data structure). Queue is opened from both the end that makes it flexible and fast for inserting and deleting elements in data structure. There are different terminologies that we are using in queue to understand its representation-
- Enqueue (Insertion operation in queue)
Enqueue operation of queue inserts elements in a queue. Insertion of elements in the queue done from the rear end.
- Dequeue (Deletion operation in queue)
Deletion operation of the queue removes elements from the queue. Deletion will be done from the front end of the queue.
The representation of the queue looks like the arrangement of elements in the list where both the ends are opened. Pictorial representation of the queue in data structure depicted below :
There are some cases when we are performing deletion and insertion in a queue. We have to consider two pointers in the queue i.e, front pointer and rear pointer.
Case 1 : If queue is empty that means there is no element in queue.
Front > Rear or Front = Rear = -1
Case 2 : If queue is not empty that means there is at least one element in the queue.
Front < Rear
Case 3 : If there is only one element in the queue.
Front = Rear
Case 4 : For enqueue operation
Rear = Rear + 1
Difference Between Stack and Queue Data Structures
In this section we are discussing the key differences between stack and queue data structures in the tabular format.
| Serial No. | Stack Data Structure | Queue Data Structure |
| 1 | Like a stack of books as to add/remove from the top | Like a line at a ticket counter as first in, first out |
| 2 | Last item goes out first (LIFO) | First item goes out first (FIFO) |
| 3 | Push to add, Pop to remove | Enqueue to add, Dequeue to remove |
| 4 | Only one end is used (the top) | Uses two ends – front and rear |
| 5 | Think of undo buttons | Think of waiting lists |
| 6 | Removes the newest item | Removes the oldest item |
| 7 | Useful in recursion | Useful in scheduling |
| 8 | Memory grows upwards (usually) | Memory flows sideways (conceptually) |
| 9 | Easier to reverse things | Hard to reverse things directly |
| 10 | Works like a coin stack | Works like a printer queue |
| 11 | Access only top element | Access front and rear elements |
| 12 | Not ideal for fairness | Perfect for fairness (first come, first serve) |
| 13 | Good for backtracking | Good for task processing |
| 14 | No need to keep track of front | Must keep track of both ends |
| 15 | Can be implemented with array/linked list | Same, but needs handling two ends |
| 16 | Examples: undo in editors, browser history | Examples: print jobs, call center lines |
| 17 | Removes from where it adds | Removes from a different place than it adds |
| 18 | Simple and fast for recent item access | Great for orderly task handling |
| 19 | Top element is always visible | Front and rear are both important |
| 20 | Ideal when order doesn’t matter much | Ideal when maintaining order is critical |
Conclusion
Understanding the difference between queue and stack data structures is very important for any beginner or aspiring developer. While both are linear structures which is used to store data, their order of processing makes them useful for totally different problems. A stack follows the LIFO (Last In First Out) rule and is great for situations like undo features or function calls. On the other hand, a queue uses FIFO (First In First Out), perfect for managing tasks in the order they arrive, like customer service lines or CPU task scheduling. Once you know when to use which, you can write more logical and efficient code that solves real-world problems smoothly.
Frequently Asked Questions
What is the main difference between queue and stack data structures?
The main difference is in how they remove elements. A stack removes the most recent item (LIFO), while a queue removes the oldest item (FIFO).
Why is understanding the difference between queue and stack data structures important?
It’s important to understand the difference between queue and stack data structures because their structures are differ with each other.