Hierarchical Database Model

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Of the three databases mentioned above, it is the oldest. According to its inception, it is an advanced adaptation of the flat-file database system because its fundamental design includes a straightforward data relationship architecture. The perspective on a hierarchical database model is the parent-child connection. Although a parent identity can contain multiple child entities, the word ""hierarchical"" is derived from the simultaneous acceptance of the restriction that a kid entity can only have one parent, who is either the mother or the father. For this reason, all the database interacts forming a hierarchy traced back to one root. Moreover, this model is often observed as an upside-down tree, where the entity at the top viewed as a root and as such all other objects originate from the source (Connolly & Beg, “Database systems” 4th.E. d)

The major challenge with this type of model is the increased risk of data variation in terms of trends and formatting styles. We consider using customer to demonstrate this case since a separate “buyer” table must exist for each commodity line due to the fact that a child entity cannot have more than one parent. However, there is a higher probability that there are many customers or buyers who purchased more than one type of product (Connolly & Beg, “Database systems” 4th.E. d). Definitely, information about those product users must exist in more than one table leading data redundancy.

Another issue of focus with this model is its inflexibility. For example, if the database is limited to four commodity lines. Adding a new item line into the system would require redesigning the database just because all the relationships must be defined once more. Finally, another issue of concern with the hierarchical model is in the child/parent interaction restriction. Every child is objected to having a single parent. Therefore, in the example above, it is difficult to add new buyers who have not purchased any new commodity yet. To overcome some of the limitations in the hierarchical model, the network model must be predefined.

Network Database Model

This database management system uses a data model similar to Hierarchical database management systems. In general, the difference is that the tree structure in the Network models can have more parent to several children relational model. Its basic structure is based on records/sets, and most of these databases use SQL for execution of their data. Network database management systems perform to be very adaptable in spite of being rarely used. They were very commonly used in the1950s and 1960s (Hernandez, “what is database” 17). Fetching an item in this database system requires the code to traverse the entire data set which is quite difficult.

Furthermore, this database system is an improvement to its mother, the hierarchical model. In the network system, a child entity can have a chance of having more than one parent. This means that, the data outline can be assumed as several inverted trees linked up by branches as opposed to the individual inverted tree characteristic of the hierarchical model. As discussed above the network database model eliminates the need to hold several “buyers” tables (Hernandez, “what is database” 17).

Data in this type of model can be fetched from an entity as opposed to the hierarchical model which requires access from the root entity. The relationships between items happen through unique set data structures. Although the entities are not copied or duplicated, a novel set structure is required to enhance each of the one-to-many relationships. Similarly, to the hierarchical model, this system model is also navigational.

It poses big challenge in complex designs since every user has to understand the database structure in order to use it. Moreover, with a predefined structure like in the hierarchical model, altering the structure of the database becomes a difficult job. The relational model eliminates many of these problems presented in the above-discussed system model.

Relational Database Model

These database management systems are very efficient in terms of data storage and execution. Today, they are widely used in many organization and companies to store various data and information. Moreover, they are believed to be relatively easy and quite efficient to use (Hernandez, “what is database” 17). The database systems are named so because of the characteristic of normalizing the data which is usually stored in rows and columns. The relational design relies on normalizing data in the set tables. The data in one table can be similar to the one in the same table or other tables which have to be correctly organized by merging one or more tables. This can be naturally achieved by consolidating two or more tables to one, making an efficient data retrieval. Relational models less useful to other models; however, this may not be a challenge in their processing power and memory found in upcoming computers. Data in this type of model is stored in predefined fixed patterns and is usually executed using Structured Query Language (SQL). These database management systems include Oracle, MS SQL Server, IBM DB2, SQLite, and PostgreSQL.

The relational model is based on the mathematical set theory. In this model, “data is stored in packages which are perceived by the user as relations” (Hernandez, “what is database” 17). The relations are composed of tuples (rows) and attributes (columns). A row identifies each record with a unique value. The order of the rows and columns defines the data storage capacities. Therefore, these system management models are independent of physical implementation, a quality that makes them more preferable to the hierarchical and database models.

Relationships in this model can be one-to-one, one-to-many, or many-to-many. Regardless of the type of relationship, the model is visible to the user i.e.; the user does not need to understand the physical pattern of the database in order to use it. Relational databases also have their challenges.

The variability of the relational model is defined by the price of performance speed since the relationships are not predefined like in the case of hierarchical and network databases. Furthermore, a flexibility of the models introduces the complexity of enforcing integrity constraints. However, the existence of clear rules for imposing integrity assures that database integrity can be attained (Mannion, “Application development & design” 17).


To sum it up, the above discussion provides a concise analysis of the influential differences between hierarchical, network and relational database models. It is important to note that although the relational model is superior to its parental origin, there are situations that would demand the use of the older models, i.e. where the application is simple and not likely to change. It is found/ established that there exist main differences across the hierarchical, network and relational database models. Similarly, all the databases access is Navigational.

Usually all models are manipulated and altered to adequately accommodate several data and analysis in cases where emergency situations occur in the organization. They are accessed from the root. Any user is objected to understand and interpolate the database structure navigation accurately. Since database access starts from an entity, the general user is expected to understand and interpret the database structure confidently.

The database structure is transparent to the user and performs faster because it is well predefined. This simply means that the model is perfect in its operation. Unfortunately, the system is slower because of the arbitrary flexible structure. Furthermore, DBMS is not compatible with the other two models thus changes to the database structure must be reflected in the application to achieve a defined functionality.

The database structure is transparent and does not allow query language unless it is predefined in the desired application. Any user needs to know the database structure in order to query information. Versatile query language involves the ability to run ad-hoc queries. The data integrity Plagued with redundancy in respect to the child/parent limitations are less redundant than those in hierarchical model.

Since the network model is navigational, it becomes difficult to keep integrity as the database complexity increases and the general logic rules guarantee imposition of its constraints. Changes to the edifice are difficult to implement because the entire structure is predefined. The rationale is that they are easy to execute since the edifice is transparent to the user and the application.


About.com: Databases (n.d.). Retrieved December 29, 2009, from http://databases.about.com/

Chapter 1. Retrieved July, 00 from Safari Tech Books Online on the World Wide Web

Connolly, T. & Beg, C. (2005). Database systems: A practical approach to design, implementation, and management, (4th ed.). Harlow: Addison Wesley.

Hernandez, M. (17). What is a relational database? Database design for mere mortals A hands-on guide to relational database design,

John H. Porter Research Associate Professor, Department of Environmental Sciences, University of Virginia.1......Relational Database Management Systems

Mannion, M. V. (2001). Database: Application development & design. New York: McGraw-Hill.

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