Hierarchical Database Systems, as the name suggests, consist of databases where records are stored in a tree-like or parent-child structure. One parent node can have one or more child nodes. However, a child node can have only a single parent node. Thus, a Hierarchical Database System can have one-to-one and one-to-many relations, but not many-to-many relations. A record of employees linked to their respective reporting managers can constitute a hierarchy. A website sitemap is another example of a hierarchy. Similarly, the folder structure in your machine can also be represented hierarchically.
In this article, you will gain information about Hierarchical Database Systems. You will also gain a holistic understanding of the history and examples of Hierarchical Database Systems. It will also provide information about the advantages and disadvantages of Hierarchical Databases.
Table of Contents
What are Hierarchical Database Systems?
In a Hierarchical Database System, the data is stored as records (like in relational database systems). However, each record has a parent ID that lends it to the tree structure. The first record is known as the root record.
Consider the following example of a database containing 3 tables: Company, Departments, and Employees.
|ID||Company Name||Parent ID|
|ID||Department Name||Department Description||Parent ID|
|10||R&D||Innovate new products||1|
|11||Finance||Manage Working Capital||1|
|12||HR||Define and maintain org. values||1|
|13||Sales and Marketing||Create the brand and sell the products||1|
|ID||Employee Name||Age||Parent ID|
As you can see, each record in each table has a parent ID that links to a record in its parent table. The Company table has only one record and it is the root table. The Departments table has departments belonging to the company, and the employees table has employees belonging to each department. As you can see, each record (except the root node) has only one parent.
In an actual hierarchy, this data may be represented as follows:
In practice, the parent-to-child relationship is implemented through pointers/indexes and parent and child records are stored close to each other on a storage device, minimizing the time to access records.
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History of Hierarchical Database Systems
Hierarchical databases are well-suited to the tape storage systems used by mainframe computers in the 1970s. It was quite popular among organizations using this storage system back then. However, it lost popularity after the introduction of the relational model. The 1990s saw some resurgence of the hierarchical database model example through XML.
Examples of Hierarchical Database Systems
IBM’s Information Management System (IMS) is an example of a hierarchical database system. Windows Registry is another such example. Another example that you may be aware of is XML data storage that we discussed earlier. XML has a root node enclosing one or more child nodes. Each child node can further enclose one or more child nodes. The sitemap of any website (which we considered as an example of hierarchical data earlier) is generally in the XML format.
For example, here’s the sitemap of a website (iotespresso.com).
As you can see, there is a parent node (sitemap index), which contains 3 child sitemap nodes (post-sitemap, page-sitemap, and category-sitemap).
Advantages of Hierarchical Database Systems
Simplicity is perhaps the greatest advantage of Hierarchical Databases. Since each record has only one parent, traversing through the database is very fast. There is referential integrity built into a hierarchical database. Thus, a record in a child table must be linked to a record in the parent table. Consequently, if a record is deleted in the parent table, corresponding child records also get deleted.
Several programming languages provide support for dealing with tree-type data structures, making dealing with Hierarchical Databases example very simple.
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Disadvantages of Hierarchical Database Systems
The rigidity of this database is a big disadvantage. Since a child can have only one parent, often redundant records have to be introduced to properly explain some relationships. For example, in the above organizational structure, if Siddhi was also taking part in some work in the Finance department, a new entry for her would’ve had to be created, with the Finance department being the parent. Thus, there would be two Siddhis with different IDs in the database, although they represent the same person.
Similarly, if a child has no parent assigned, then it becomes difficult to add the child record to this database. A temporary dummy parent record would have to be created. For example, consider a fresher joining the company and going through the training. His/her department would be allotted only after training. In such a case, it is difficult to add the record of that employee to the hierarchical database unless a dummy department like ‘Training’ is created.
Reorganizing data within a hierarchical database can be very difficult because the parent-child relationships should not be disturbed. If someone wants to introduce a new relationship in the future, say ‘Category’ between ‘Departments’ and ‘Employees’, then reorganizing the entire database would be quite a task. Even if you do add the new relationship, all programs and applications accessing this database need to be modified to incorporate this new relationship.
Another disadvantage is that the scope of such a database is quite limited. Not every data is hierarchical and you’d ultimately have to use other systems (like relational data model) to represent your data. Also, there is no defined standard for hierarchical database systems, so the implementation differs for each system that you come across.
In this article, you have learned about Hierarchical Database Systems. This article also provided information on the history and examples of Hierarchical Database Systems. We also looked at the advantages and disadvantages of this database system. You need to weigh your options before opting for a hierarchical database system, and determine if it is indeed the best system to store your data. Hopefully, this article provides you with help on that front.
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