Stack vs Queue | Difference Between Stack And Queue | Data Structures And Algorithms | Simplilearn

This video is based on Stack vs Queue in data structure. It will help you understand the Difference Between Stack And Queue in details. This tutorial covers the basic data manipulation operations with the help of real life examples along with few more parameters. So, let's get started!

The topics covered in this video on Stack vs Queue are:
00:00 Introduction to Stack vs Queue
00:51 Differences in Stack vs Queue
06:14 Quiz on Stack vs Queue

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What is Queue in Data Structure?
A queue is an ordered collection of items in which new items are added at one end, referred to as the back,and current items are removed at the other end, referred to as the front.When an element joins the queue, it begins at the back and works its way to the front, waiting to be the next element to be removed. The item in the queue that was added most recently must wait until the end of the collection. At the front of the collection is the object that has been there the longest. First In First Out (FIFO) is another term for this ordering approach.

What Is a Data Structure?
The short answer is: a data structure is a specific means of organizing data in a system to access and use. The long answer is a data structure is a blend of data organization, management, retrieval, and storage, brought together into one format that allows efficient access and modification. It’s collecting data values, the relationships they share, and the applicable functions or operations.

Why Is Data Structure Important?
The digital world processes an increasing amount of data every year. According to Forbes, there are 2.5 quintillion bytes of data generated daily. The world created over 90 percent of the existing data in 2018 in the previous two years! The Internet of Things (IoT) is responsible for a significant part of this data explosion. Data structures are necessary to manage the massive amounts of generated data and a critical factor in boosting algorithm efficiency. Finally, since nearly all software applications use data structures and algorithms, your education path needs to include learning data structure and algorithms if you want a career as a data scientist or programmer. Interviewers want qualified candidates who understand how to use data structures and algorithms, so the more you know about the concepts, the more comfortably and confidently you will answer data structure interview questions.

[exiphykiller]

I think the answer to your question is Linked List.
Because in arrays we cannot decide the size at run time. Which means if our array gets completely filled, we will have to copy the contents of created array into larger array. And this will take twice the memory as of array.

[prasadsawant]

I think the answer is array. Because linked list might need extra memory to store pointers.

[shadabmuzafarkhil]

The answer is )
The linked list implementation (dynamic)
Because queue Data structure is a bit more easily to implement and store ‘Delete and remove the data
Regards (Ahmad shadab )

[whatwatch]

What software you use to make informational videos like this??

[mansishmahakul]

Q 》 Array Implementation would be the answer .

[sanketjadhav]

I guess the answer is Linked List. Because due to its dynamic nature, it's size can be increased at any instance of our program.

[mthokozisikhumalo]

Based on my comprehension, answering this question with this superficial information was hard.. Array implementation has more effective close bounds in set..

[shadabmuzafarkhil]

I think the real-life example didn’t much properly because if we want to remove a book we can remove it from the middle-end top anyway and from the line of the people for a ticket cabin we can remove people from anywhere by asking them so at all I think the real-life example is not matching at all
Regards

[varshask]

I guess linked lists because it's size is not priorly defined

[harshnaikade]

I think the answer is Linked List.
Linked list allows us to manage memory more efficiently due to it's property to increase size at any instance of program.