Welcome to our blog where we delve into the world of hierarchical database systems. In this post, we will go into detail about what hierarchical database systems are, how they work, and their benefits. If you have any questions about the topic, we hope to provide you with the knowledge you need to better understand this complex and fascinating technology. Hierarchical databases have been around since the 1960s and despite the rise of newer database models, are still used today. So, come along with us as we explore everything you need to know about hierarchical database systems.
Introduction
A Hierarchical Database System stores records in a tree-like structure, with each record linked to a parent record through a parent ID. The root record is the first record, and each subsequent record has a single parent but can have multiple children. This system is ideal for representing one-to-many relationships but not suitable for many-to-many relationships. It was popular in the 1970s with mainframe computers as it worked well with tape storage systems. Although it lost popularity with the introduction of the relational model, it still has applications in areas like banking, healthcare, and telecommunications, where performance and availability are essential. Overall, Hierarchical Database Systems remain relevant in specific settings and can be a useful tool in managing certain types of data.
History
Hierarchical database systems first emerged in the 1960s in response to the need for efficient data management on mainframe computers using tape storage systems. This type of database model allowed for the storage of records in a tree-like structure w0.ith each record having a unique parent, but each child record only has one parent. However, they experienced a revival with the development of XML in the 1990s. Today, some applications continue to utilize hierarchical database systems where a hierarchical structure is ideal, such as in website sitemaps and computer folder systems.
 Structure of Hierarchical Database Systems
The hierarchical database system organizes its structure into a tree-like formation, establishing parent-child relationships between each data piece. Each hierarchy record can have one or more child records, linked to its parent record. The root node is the topmost record and can connect to multiple child nodes. Retrieving data from this system is simple, but it may not be suitable for managing complex data relationships or alterations in data structures. The records hold the data, with each field containing one value, and its type determines which fields it includes. In the 1960s, IBM developed the first database model, known as the hierarchical database model, which requires traversing the entire tree from the root node to retrieve data.
Example of Hierarchical Database Systems
In the 1970s, IBM’s Information Management System (IMS) was widely used as a Hierarchical Database System. Banks, airlines, and insurance companies utilized IMS for managing and storing vast amounts of data, specifically for transaction processing on mainframe computers. In IMS, data is organized into hierarchical records, with each record having a parent-child relationship. Each child record can have only one parent record, but a parent record can have multiple child records. IMS uses a special language called DL/I (Data Language/I) to manipulate and retrieve data. Today, IMS is still widely used in some industries but has been largely replaced by relational database systems in other areas.
Advantages of Hierarchical Database Systems
Hierarchical database systems offer a significant advantage of quick and efficient data retrieval. This is because the data is organized in a structured and predictable manner through a parent-child relationship. Adding or deleting information is also easy in these types of databases. Another advantage is the predictable data structure, which makes it easier to understand and navigate.
Disadvantages of Hierarchical Database Systems
Despite the advantages of hierarchical database systems, there are also several notable disadvantages. One of these disadvantages is limited flexibility. Hierarchical databases are not as suitable as other types of databases for handling complex data relationships or changes in data structures. They also lack support for complex data manipulation operations like data mining and data aggregation. Maintenance and updating can also be challenging since changing the data structure could impact the entire database. Moreover, hierarchical databases are not compatible with other database models, which limits their interoperability with other systems and applications. Finally, the lack of widespread usage of hierarchical databases means that there are no established standardizations or best practices, resulting in inconsistent use and management of these databases.
Comparison with Relational Database Systems
When comparing hierarchical database systems to relational database systems, there are notable differences to consider. Relational databases store data in tables connected through relational links, while hierarchical databases organize data in a parent-child structure, creating a tree-like formation. While hierarchical databases are simpler to use and optimize, they lack flexibility and require hard-coded linkages. Relational databases, though more complex, allow for more natural data entry and manipulation. They are also less dependent on the applications that use them and have easy data backup and retrieval options. However, in recent years, relational databases have become more popular due to their flexibility and ease of use.
Applications of Hierarchical Database Systems
Hierarchical Database Systems have various uses and applications. Their inherent hierarchical structure that goes well with disk storage systems makes them commonly used as physical models. One of the notable applications is in semantic models where real-world events are hierarchical in nature, such as in biological and social structures.
Hierarchical Database Systems were also the first to offer data security and data integrity features. However, this database model lacks flexibility, as changes in new tables or segments can yield complex system management tasks. In addition, it has no specific standard implementation, and many common relationships do not conform to the 1-to-N format as required by the hierarchical model.
Hierarchical Data Represented as Relational Tables
In this method, we transform a hierarchical database into a relational database model by representing each level of the hierarchy as a separate table with a foreign key linking it to its parent table. Each table in the relational database represents a level of the hierarchy with its own fields or attributes. This approach allows for more flexibility and easier handling of complex data relationships and changes in data structures. It also enables the use of SQL to perform complex data manipulation operations such as data aggregation or data mining. A widely accepted method for managing complex data relationships in a more efficient and scalable way is representing hierarchical data as relational tables.
Future of Hierarchical Database Systems
The future of the Hierarchical Database seems bright. Although it lost popularity with the introduction of the relational model, in the 1990s it saw a resurgence through XML. With the growth of big data and the Internet of Things (IoT), Hierarchical Databases have found new applications. As these systems can handle large amounts of data in a tree-like structure. Thus, it will continue to be an essential tool for managing hierarchical data.
