Types of Data Structures: A Guide to Organizing and Managing Data Efficiently

A linear data structure is a type of data structure where data is arranged one after the other, in a straight line. Each item comes after the previous one and before the next one. Because of this order, it’s simple to go through the data from the beginning to the end, or even in reverse if the structure allows it.

This type of structure is useful when you want to process data in a specific order. You always know what comes next, and that makes it easier to search, add, or remove elements, depending on which linear structure you’re using.

Several types of linear data structures exist, and one of the most commonly used is the array.

• Arrays

An array is a group of elements arranged sequentially in memory. Each element is assigned a specific position, known as an index, which starts at zero. If you know the index, you can directly access the corresponding element.

Arrays are fast for reading data. They’re simple to use, but there are some limitations. For one, the size is usually fixed from the start, so you can’t keep adding new elements forever. You’d have to make a new array if you run out of space. Also, adding or removing items in the middle of an array takes time because the other items may need to be moved.

Where arrays come in handy:

They’re perfect for storing things like lists of numbers, names, or even character stats in a game or data points in a simulation.

• Linked Lists

A linked list is a more flexible type of data structure where each item, or node, has two parts: the actual data and a reference (or pointer) to the next node. This makes linked lists more dynamic. They can grow or shrink as needed. The main advantage here is flexibility. You can easily add or remove items without having to worry about the size of the list ahead of time. 

The downside, though, is that accessing data is slower than with arrays. Since you have to start at the beginning and follow the pointers one by one to get to the item you want, it takes more time. So, linked lists give you flexibility, but it’s at the cost of speed when it comes to finding specific items.

Where linked lists come in handy:

They’re great when you don’t know the size of your data set upfront or when it changes often. For example, if you’re managing a to-do list or handling a series of user inputs that could keep growing or shrinking, a linked list is perfect for that kind of dynamic situation.

• Stacks

A stack is a linear data structure that follows the Last In, First Out (LIFO) rule. This means the most recently added element is the first one to be removed.

Key points about stacks:

• Push: Adds an item to the top of the stack.
• Pop: Removes the top item from the stack.
• Peek: Views the top item without removing it.

Applications of Stacks:

It is useful in scenarios where you need to track a sequence of operations, such as undo/redo actions in a text editor or browser history.

• Queues

A queue is a linear data structure that works based on the First In, First Out (FIFO) method. This means the first element added is the first one to be removed, similar to people standing in line, where the first person to join the line is the first to be served.

Key points about queues:

• Enqueue: Inserts an item at the back of the queue.
• Dequeue: Takes an item out from the front of the queue.
• Peek: Views the front item without removing it.

Applications of Queues:

It is used in scenarios where items need to be processed in order, such as handling tasks in a printer queue or managing requests in a server.