What Is Meant by Non Primitive Data Structure?


Larry Thompson

What Is Meant by Non Primitive Data Structure?

Data structures are the building blocks of any program or application. They allow us to organize and store data efficiently, making it easier to manipulate and retrieve information. In programming, there are two types of data structures: primitive and non-primitive.

Primitive data structures are the basic data types provided by programming languages. These include integers, floating-point numbers, characters, and booleans. They are simple and can hold only one value at a time.

Non-primitive data structures, on the other hand, are more complex. They can hold multiple values and have various operations defined on them. Non-primitive data structures are built using primitive data types and other non-primitive data structures.

Types of Non-Primitive Data Structures:

1. Arrays:

An array is a collection of elements of the same type arranged in a contiguous memory block.

It allows us to store multiple values under a single name.

We can access elements in an array using their index position. Arrays can be one-dimensional, two-dimensional, or multi-dimensional depending on the number of dimensions needed to represent the data.

2. Linked Lists:

A linked list is a linear data structure where each element (node) contains a reference to the next element in the list.

It is composed of nodes that contain both data and a pointer to the next node.

The advantage of linked lists is that they allow dynamic memory allocation as they do not require contiguous memory blocks like arrays do. Linked lists come in different types such as singly linked lists, doubly linked lists, and circular linked lists.

3. Stacks:

A stack is a linear data structure that follows the Last-In-First-Out (LIFO) principle. It has two main operations: push (adds an element to the top of the stack) and pop (removes the topmost element from the stack).

Stacks are commonly used in programming languages to handle function calls, recursion, and expression evaluation.

4. Queues:

A queue is a linear data structure that follows the First-In-First-Out (FIFO) principle. Elements are added at one end (rear) and removed from the other end (front).

Queues are often used in scenarios where elements need to be processed in the order they arrive, such as handling requests or scheduling tasks.

5. Trees:

Trees are non-linear data structures that consist of nodes connected by edges.

They have a hierarchical structure with a root node at the top and child nodes branching out from it.

Trees have many variations, including binary trees, binary search trees, AVL trees, and B-trees. They are widely used for organizing hierarchical data like file systems and representing hierarchical relationships.

6. Graphs:

A graph is a non-linear data structure composed of vertices/nodes connected by edges/links. Graphs can be directed or undirected, depending on whether the edges have a specific direction or not.

Graphs are used to represent complex relationships between entities and find optimal paths in various applications like social networks, maps, and transportation systems.


In conclusion, non-primitive data structures are essential tools for organizing and managing large amounts of data efficiently. Arrays, linked lists, stacks, queues, trees, and graphs provide different ways of storing and accessing data, depending on the requirements of a program or application.

By understanding these non-primitive data structures and their operations, programmers can design more efficient algorithms and solve complex problems effectively.

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