Introduction to Non-Primitive Data Structures

Non-primitive data structures, also known as composite data types, are collections of data elements that can be of different types and sizes. Unlike primitive data types, which store single values, non-primitive data structures can store and organize multiple values or objects in a structured manner. These structures facilitate efficient data storage, retrieval, and manipulation, enabling programmers to tackle complex problems effectively.

Linear Data Structures:

• Linear data structures organize elements in a sequential manner, where each element is connected to its previous and next elements.
• Elements are accessed and processed in a linear sequence, typically starting from one end and moving towards the other.
• Examples of linear data structures include arrays, linked lists, stacks, and queues.

Non-Linear Data Structures:

• Non-linear data structures do not organize elements in a sequential manner. Instead, they allow elements to be arranged in a hierarchical or interconnected manner.
• Elements in a non-linear data structures can have multiple connections or relationships with other elements, forming complex structures.
• Examples of non-linear data structures include tress and graphs.
• Non-linear data structures are useful for representing relationships and hierarchies, such as hierarchical data, network connections, and various types of dependencies.

Differentiate between Linear and Non-Linear Data structures

Organization:

• Linear data structures organize elements in a linear sequence, where each element has a direct successor and/or predecessor.
• Non-linear data structures organize elements in a hierarchical or interconnected manner, allowing for multiple relationships between elements.

Access Pattern:

• In Linear data structures, elements are typically accessed and processed sequentially, either from the beginning to the end or vice versa.
• In non-linear data structures elements may be accessed in various ways, depending on the specific structure and relationships between elements. For example, in trees, elements may be accessed in a hierarchical manner, while in graphs, elements may be accessed based on specific paths or connections.

Hash-Based Data Structures:

Heap-Based Data Structures:

Composite Data Structures: