Hierarchical Data Model

Introduction

A hierarchical data model represents data in a tree-like structure, with parent-child relationships.

Components

• Root Node: The topmost node in the hierarchy.
• Parent Node: A node that has child nodes.
• Child Node: A node that is dependent on a parent node.

Characteristics

• One-to-Many Relationships: A parent node can have multiple child nodes, but a child node can have only one parent node.
• Tree-Like Structure: Data is organized in a hierarchical structure, with each node having a specific relationship to its parent and child nodes.

Benefits

• Simple and Efficient: Hierarchical data models are simple to understand and efficient to implement.
• Fast Data Retrieval: Data retrieval is fast, especially for queries that follow the hierarchical structure.

Limitations

• Limited Flexibility: Hierarchical data models are less flexible than other data models, such as network or relational models.
• Data Redundancy: Data redundancy can occur if data is repeated in multiple nodes.

Examples

• XML (Extensible Markup Language): A markup language that uses a hierarchical structure to represent data.
• IMS (Information Management System): A hierarchical database management system developed by IBM.