Which are 8 Most Important Data Structures in Website Design

Data Structures are the building blocks of a website. In this blog we will discuss regularly used 8 most important data structures in website design in 2021

A data structure is a special way of organizing and storing data on a computer for more efficient use. Data structures have a wide variety of applications in computer science and software engineering. Data structures are used in almost all programs or systems that are used for development. It is a basic requirement in computer science and software development field for structuring of data. In this article we will discuss 8 Most Important Data Structures in Website Design


An array is a fixed size structure that can contain elements of the same data type. It can be a set of integers, multiple floating point numbers, a series of strings, or a series of arrays.

The array is resized so that the elements in the array cannot be removed or the elements can be immediately removed from the array. It is used as a building block for creating lists of matrices, stacks, hash tables, vectors, and other data structures such as matrices.

It is used in various sorting algorithms such as insert sort, quick sort, bubble sort, and combined sort.

Linked Lists

A linked list is a sequential structure made up of a series of related items in a linear order, so that the data must be accessed sequentially and not randomly. Linked lists provide simple and flexible versions of dynamic sets.

The elements of a linked list are called nodes. Each node contains a key and a pointer to the next node, which is called the Next, and the last element of a linked list is called a String


The stack is a widely used LIFO structure (last-in-first-out-last-in-first-out) in many programming languages. This design is called "stack" because it looks like a real stack, a stack of plates. It also provides the following additional functions for checking the status of the stack for example - 

  • Peak: Displays the top of the stack without emptying the stack.
  • isEmpty: Checks if the stack is empty.
  • IsFull: Checks if the stack is full.

Stacks are used for evaluating batch expressions such as mathematical field algorithms for parsing and evaluating formulas and are also used to implement function calls in recursive programming.


Queue is a FIFO (first in first out-items placed at the top can be accessed first) structure, which can be found in many programming languages. This structure is called a "queue" because it looks like a queue in the real world-people are waiting in a queue. Using queue, you can give following commands - 

  • Enqueue: Insert an item at the end of the queue.
  • Dequeue-Remove items from the top of the queue.

Hash Tables

A hash table is a data structure that stores values, and each value has an associated key. The search becomes effecient if programmer knows the key associated with the value, plus data can be added with any size using hash tables. Hash tables uses a one-to-one mapping between values ​​and keys when stored in a table.

However, this method has problems when there are a large number of key-value pairs. Hash tables contain lot of records which could be a challenge for a regular computer system in storing that data.


A tree is a hierarchical structure in which data is organized hierarchically and linked to each other. This structure is different from a linked list, and in a linked list, items are linked in a linear order. In the past few decades, various types of trees have been developed to suit certain applications and meet certain restrictions.

Some examples are binary search trees, B-trees, treap, red-black trees, expanded trees, AVL trees, and n-ary trees. Binary search tree Binary search tree (BST), as the name suggests, is a binary tree where data can be found.


A heap is a special case of a binary tree, in which the top node is compared with its child nodes and their values ​​and arranged accordingly.
An example of minimum heap attribute is 

  • Minimum heap: The father's key is less than or equal to his child's key. The root will contain the minimum value of the heap. 
  • Maximum heap: The key of the parent item is greater than or equal to the key of its child. This is called the maximum heap attribute. The root will contain the maximum value of the heap.

It is used to implement priority queues, because priority values ​​can be sorted according to heap attributes, and arrays can be used to implement heaps.


A graph consists of a finite set of vertices or nodes and a set of edges connecting these vertices. The order of the graph is the number of vertices in the graph. The size of the chart is the number of sides on the chart. If two nodes are connected to each other by the same edge, the two nodes are said to be adjacent.

  • If all edges of graph have a direction, which indicates the initial vertex and the final vertex, then the graph is called a directed graph.
  • If all edges of graph have no direction, it is called an undirected graph. It can move in both directions between two vertices.
  • If a vertex is not connected to any other node in the graph, it is said to be isolated.