Comparison of Hierarchical and Relational Databases

Hierarchical and relational databases are two different manners in which to store and organize data that also allow management and utilization of that data. There are essential aspects that any database should be able to provide, those of creating, reading, updating and deleting data. Upon becoming familiar with how each database is set up, it is important to look at the advantages and disadvantages of each model in determining which type of database one would want to utilize. The hierarchical database is one of the oldest types of database models. It is structured with parent/child relationships, where one parent category of data can have many children categories of data but any child category of data can only have one parent (Hsiao, 1992). Stephens (2009) also describes this as one-to-many relationships. The parent and child categories are known as segments and within each segment the data is categorized into fields (Hsiao, 1992). Since the different categories of data in the parent/child relationship are already structured along a hierarchical path, those relationships are joined implicitly.
Some advantages of the hierarchical database are that it can be accessed and updated rapidly due to the one-to-many structure and the fact that relationships are implicitly joined. (Heberling, 2008). Given that, as Stephens (2009) explains, one would want to utilize this database when working with data that is naturally hierarchical, to take advantage of the inherent joins. Furthermore, this is a preferred option when the queries or operations need to be performed with the data can take advantage of the hierarchical structure. Jao and Hier explain how physicians are able to maintain accuracy and completeness of problem and medications lists within electronic medical records by the development of the Problem List Expert (PLE). The PLE uses three linked database tables, a medication data dictionary, a problem data dictionary, and a medication-problem relationship table.