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Hierarchical Model in DBMS - GeeksforGeeks

Last Updated : 12 Feb, 2025

Database models are critical frameworks in database management systems, dictating how data is structured, stored, and accessed. Among these, the hierarchical model stands out for its tree-like structure where data is organized in parent-child relationships, resembling a family tree. This model, significant in the early development of database systems, enables efficient data retrieval through predefined pathways. Despite its age, the hierarchical model is still pertinent in modern applications that demand rigid hierarchical structures, such as XML data processing and organizational charts. Its capability to manage complex hierarchies effectively makes it invaluable for specific scenarios where performance and data order are prioritized.

• The hierarchical model is a type of database model that organizes data into a tree-like structure based on parent-child relationships. Each record, or "node," holds data and links to subordinate nodes, establishing a one-to-many relationship from the parent node to its children.
• In a hierarchical database, data is represented visually as a tree. The root node at the top represents the starting point, and branches extend downwards to child nodes, illustrating the relationships and flow of data access. Each child node has only one parent but potentially multiple children, creating a strictly defined structure that enhances the speed and simplicity of data navigation.
• The hierarchical model was developed in the 1960s, primarily driven by the need for efficient data storage and quick data retrieval systems in large-scale information processing, like the systems used by IBM. It was one of the first database models to be created, offering a solution that was more systematic and flexible than the flat file storage systems previously in use.
• This model, while somewhat limited by its rigidity and the complexity of implementing changes to the database structure, was crucial in the evolution of data storage methodologies and still influences modern database architectures that require structured hierarchical data management.

The hierarchical model organizes data in a manner that mirrors a tree structure with a single root, facilitating straightforward data storage and retrieval processes.

• Data Storage: In the hierarchical model, data is stored in records that are linked to form a structure resembling an organizational chart. Each record is a node that has links to its children but only one parent, except for the root node, which has no parent.

• Data Retrieval: To retrieve data, the process starts at the root node and traverses down through the branches to the desired child nodes. This predefined path makes data retrieval fast, as it eliminates the need for searching across unrelated nodes.

• Content Management Systems (CMS): Many CMSs use hierarchical databases to manage and organize content such as pages, articles, and media files in a structured manner. This allows for efficient retrieval and management of content that is nested within categories and subcategories.

• Organizational Structures: Businesses often utilize hierarchical databases to mirror their organizational charts. This helps in efficiently managing employee records, departmental data, and company resources that follow a clear hierarchical structure.

• File Systems: Operating systems often employ a hierarchical model to manage files and directories. This structure allows users to navigate through folders and find files easily, following a clear path from a root directory to subdirectories and files.

• Geographic Information Systems (GIS): Hierarchical databases are used in GIS to manage spatial data that is layered as in the case of maps where different layers (like terrain, roads, landmarks) are organized hierarchically.

• Network and Telecom Management: Hierarchical databases facilitate the management of extensive network configurations and telecom inventories where elements are structured in a hierarchical fashion, from network segments to individual switches and routers.

Example 1: Consider the below Student database system hierarchical model.

In the above-given figure, we have few students and few course-enroll and a course can be assigned to a single student only, but a student can enroll in any number of courses and with this the relationship becomes one-to-many. We can represent the given hierarchical model like the below relational tables:

FACULTY Table

STUDENT Table

Example 2: Consider the below cricket database system hierarchical model scheme.
 

Here, in this example, for each player, there are some set of positions (P_POSITION) he plays, a set of places (P_PLACE), and also a set of birthdates (P_BDATE) of the players. In the above figure, each node represents a logical record type and is displayed by a list of its fields. The child node represents a set of records that are connected to each record of the parent type, which is due to a many-to-many relationship is from child to parent. In the above, figure, the root node PLAYER states that for every player there will be a set of positions, a set of places (only one), and a set of birthdates (which is only one). 

• Simplicity: The tree-like structure of the hierarchical model is intuitive and easy to understand, which simplifies the design and navigation of databases. This structure clearly defines parent-child relationships, making the path to retrieve data straightforward.

• Data Integrity: Due to its rigid structure, the hierarchical model inherently maintains data integrity. Each child record has only one parent, which helps prevent redundancy and preserves the consistency of data across the database.

• Efficient Data Retrieval: The model allows for fast and efficient retrieval of data. Since relationships are predefined, navigating through the database to find a specific record is quicker compared to more complex models where paths are not as clearly defined.

• Security: Hierarchical databases can provide enhanced security. Access to data can be controlled by restricting users to certain segments of the tree, which makes it easier to implement security policies based on data hierarchy.

• Performance: For applications where relationships are fixed and transactions require high throughput, such as in banking or airline reservation systems, the hierarchical model offers excellent performance and speed.

• Structural Rigidity: The biggest limitation of the hierarchical model is its structural rigidity. Once the database is designed, making changes to its structure, such as adding or modifying the relationships between records, can be complex and labor-intensive.

• Lack of Flexibility: This model does not easily accommodate many-to-many relationships between records, which are common in more complex business applications. This limitation can lead to redundancy and inefficiencies when trying to model more intricate relationships.

• Data Redundancy: In cases where a child has more than one parent, the hierarchical model can lead to data duplication because each child-parent relationship needs to be stored separately. This redundancy can consume additional storage and complicate data management.

• Complex Implementation: Implementing a hierarchical database can be more complex than more modern relational databases, particularly when dealing with large sets of data that have diverse and intricate relationships.

• Query Limitations: The hierarchical model typically requires a specific type of query language that might not be as rich or flexible as SQL, used in relational databases. This can limit the types of queries that can be executed, affecting the ease and depth of data analysis.

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