Working with Hierarchical Database Systems Simplified 101


Hierarchical Database Systems_FI

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.

Company Table:

IDCompany NameParent ID

Departments Table:

IDDepartment NameDepartment DescriptionParent ID
10R&DInnovate new products1
11FinanceManage Working Capital1
12HRDefine and maintain org. values1
13Sales and MarketingCreate the brand and sell the products1

Employees Table:

IDEmployee NameAgeParent 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:

Hierarchical Database Systems: Actual Hierarchy Example| Hevo Data
Image Source: Self

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.  

Simplify Data Transformation using Hevo’s No-code Data Pipeline

The constant influx of raw data from countless sources pumping through data pipelines attempting to satisfy shifting expectations can make Data Science a messy endeavor. It can be a tiresome task especially if you need to set up a Manual solution. Automated tools help ease out this process by reconfiguring the schemas to ensure that your data is correctly matched when you set up a connection. Hevo Data, an Automated No Code Data Pipeline, is one such solution that leverages the process in a seamless manner.

Get Started with Hevo for Free

Hevo is the fastest, easiest, and most reliable data replication platform that will save your engineering bandwidth and time multifold. Try our 14-day full access free trial today to experience an entirely automated hassle-free Data Replication!

Experience an entirely automated hassle-free Data Pipeline experience. Try our 14-day full access free trial today!

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 (

Hierarchical Database Systems: Example| Hevo Data
Image Source: Self 

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. 

What makes Hevo’s Data Transformation Capabilities Unique

Providing a high-quality ETL solution can be a difficult task if you have a large volume of data. Hevo’s automated, No-code platform empowers you with everything you need to have for a smooth data replication experience.

Check out what makes Hevo amazing:

  • Fully Managed: Hevo requires no management and maintenance as it is a fully automated platform.
  • Data Transformation: Hevo provides a simple interface to perfect, modify, and enrich the data you want to transfer.
  • Faster Insight Generation: Hevo offers near real-time data replication so you have access to real-time insight generation and faster decision making. 
  • Schema Management: Hevo can automatically detect the schema of the incoming data and map it to the destination schema.
  • Scalable Infrastructure: Hevo has in-built integrations for 100+ sources (with 40+ free sources) that can help you scale your data infrastructure as required.
  • Live Support: Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
Sign up here for a 14-day free trial!

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.

Hevo Data, a No-code Data Pipeline provides you with a consistent and reliable solution to manage data transfer between a variety of sources and a wide variety of Desired Destinations with a few clicks.

Visit our Website to Explore Hevo

Hevo Data, with its strong integration with 100+ Data Sources (including 40+ Free Sources) allows you to not only export data from your desired data sources & load it to the destination of your choice but also transform & enrich your data to make it analysis-ready. Hevo also allows the integration of data from non-native sources using Hevo’s in-built REST API & Webhooks Connector. You can then focus on your key business needs and perform insightful analysis using BI tools. 

Want to give Hevo a try? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand. You may also have a look at the amazing price, which will assist you in selecting the best plan for your requirements.

Share your experience of understanding Hierarchical Database Systems in the comment section below! We would love to hear your thoughts.

Yash Sanghvi
Technical Content Writer, Hevo Data

Yash is a trusted expert in the data industry, recognized for his role in driving online success for companies through data integration and analysis. With a Dual Degree (B. Tech + M. Tech) in Mechanical Engineering from IIT Bombay, Yash brings strategic vision and analytical rigor to every project. He is proficient in Python, R, TensorFlow, and Hadoop, using these tools to develop predictive models and optimize data workflows.

No-code Data Pipeline for your Data Warehouse