Data Structures Overview

Using data structures, computers store, organize, and manipulate information. Developing efficient and scalable software systems depends on these building blocks.

There are two general categories of data structures: primitives and non-primitives. Primitive data structures supported by the language include integers, floating-point numbers, characters, and booleans. Integers, floating-point numbers, characters, and booleans are among the primitive data structures supported by the language. A non-primitive data structure consists of a list, stack, queue, tree, or graph, while a primitive data structure consists of a single element.


As one of the most common data structures, arrays store elements of the same type. The elements of a list can be of different types, unlike a list that grows or shrinks dynamically. A stack or queue is a specialized data structure that manages the order in which elements are collected.

A graph or tree represents hierarchical relationships between data in a non-linear manner. Every node in a tree can have a child node, and each child node can have zero or more children. A graph, however, has nodes and edges that represent their relationships.

An applications performance and efficiency can be dramatically impacted by choosing the right data structure. Arrays are ideal when the size and frequency of access to elements in a data set are known in advance. When elements need to be added or removed frequently, lists are better suited when the data set size is unknown.


The knowledge of computer science is essential for software developers and computer scientists. Their importance can greatly affect the performance of an application and are the foundation of efficient and scalable software systems. It is crucial to understand the problem thoroughly before choosing the right data structure for it.