Difference Between Hierarchical Database and Relational Database

Edited by Diffzy | Updated on: August 30, 2022

       

Difference Between Hierarchical Database and Relational Database Difference Between Hierarchical Database and Relational Database

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Introduction

Databases are exactly what they sound like, accurately organized collections of data that can be accessed digitally through the relevant management systems. Not only do these database models store data but also allow features that can help represent how the elements of the data are related to each other. There are many categories of databases depending on their records, objects, and physical data. However, we will look into the two popular and oldest database models: Hierarchical database and relational database, both of which are record-based data models.

Hierarchical Database vs. Relational Database

The main difference between a hierarchical database and a relational database lies in how the data is stored i.e., the respective structures used to store the data. Hierarchical databases use a tree structure to represent data that involves parent and child nodes whereas relational databases use tables to represent data that involve primary keys and foreign keys.

Difference Between Hierarchical Database and Relational database in Tabular Form

Table: Hierarchical Database vs. Relational Database
Parameters of Comparison
Hierarchical Database
Relational database
Origin
It is a first-generation data model that was developed by IBM in 1968.
It is a second-generation data model that was developed by E.F.Codd in 1970.
Structures
Tree structures are used to store and represent data where there is a hierarchical relationship between the parent and child nodes.
Table structures are used to store and represent data where there are indexed keys to represent relationships that exist between every node.
Relations
Hierarchical database allows the implementation of one-one or one-many relationships.
a Relational database allows the implementation of one-one, one-many, and many-many relationships.
Searching
Data retrieval can be difficult as one must traverse the whole tree starting from the parent node to reach the required node.
Data retrieval is made easy through the employment of SQL techniques.
Insertion & Deletion
There is an anomaly during both insertion and deletion as the child node cannot be inserted without the parent node and the parent node cannot be deleted easily.
There is no anomaly in this kind of database, neither with relevance to insertion or deletion.
Consistency
There is a possibility of data inconsistency during such insertion and deletion operations.
Due to normalization processes, data inconsistency is avoided while simultaneously reducing complexity.
Data Independence
The hierarchical model does not provide data independence.
The relational model provides data independence.
Applications
It is popularly used in search engine operations and shopping carts.
It is popularly used in traditional software such as IBM DB2, Oracle dB, etc.

What is a Hierarchical Database?

Developed in the late 1960s, the hierarchical database model can be described as one of the oldest models of a database system to be invented and popularly risen to fame. A hierarchical database uses tree-like structures to store data and represent it. Let us look at how it works:-

  • The basic element is called a node and is connected to the other nodes by branches.
  • The nodes lie on the top or bottom of each other and are considered to be at different levels.
  • The node at the top-most will be called the root node.
  • In the event of multiple nodes existing at the top-most level, we can term them as root segments.
  • The node on the top of another node will be called the parent node while the node on the bottom will be the child node, considering these both nodes are connected by a branch.
  • Each node must have only one parent node.
  • Each parent node may have any number of child nodes.

These database models are easier to comprehend through the use of hierarchical structure and pointers that help define the branches better. Even though data retrieval can take quite some time, navigation is easier since the structure follows a pre-defined scheme throughout the database. However, data cannot be reorganized in the event that requires so. There is also increased redundancy, a result of which may lead to failure in maintaining accuracy while retrieving data.

Benefits of a Hierarchical Database

  • For applications that require mediums with linear data storage, the model will fit well and work appropriately.
  • It also works well for systems that require a one-many relationship, such as corporate databases, where there are multiple managers under one president and multiple departments or employees under one manager, and so on.
  • Any data that is on the top of the tree can be accessed quickly with ease.
  • Child nodes can be inserted and deleted easily when there are enough parent nodes established.
  • It is easy to comprehend and understand these structures when compared to other structures while understanding the flow of control, management, and authority.

Limitations of a Hierarchical Database

  • Hierarchical structures do not support many-many relationships i.e., every node in the whole tree can have only one parent everywhere. Thus, it cannot be used in applications that require two-parent nodes with one or more child nodes. Eg:- database of parents of students at school.
  • Repetitive storage in various locations and entities due to the adoption of tree-like structure.
  • Require sequential traversing i.e., the Database Management System(DBMS) must search the tree from the top to bottom in on path first and then move to the next node.
  • Any kind of data retrieval will be delayed and thus requires more memory and power consumption.

Applications of a Hierarchical Database

  • IBM information management Systems(IMS)
  • RDM mobile.
  • Windows Registry
  • XML & XAML
  • NOMAD
  • NCSS
  • Semantic models since several real-life events are organized in a hierarchical structure. Eg:- Social structure, political structures, and biological structures
  • Most corporate management-related databases or most management databases in any field will most likely follow a hierarchical model of authority and thus use this database.

What is Relational database?

The relational database was developed in 1970 and is categorized as a second-generation data model. In an attempt to compensate for the limitations posed in the previous model, the relational database model offers a more flexible structure where the structure of the database can change without affecting the data access. In this database model, Tables are used along with indexed key values to represent the relations. These structures exist separately from the physical storage structure, thus allowing changes in the physical data storage without posing the hazard of affecting the logical data structure in any way. Let us look at how this works:-

  • Data is represented in the form of a table with rows and columns
  • Each table is called a relation.
  • Each category of a column is called an attribute and each category of a row is called a record or a tuple.
  • Each row/tuple is said to hold a unique instance of data, or rather an identifier, that is known as the key.
  • The primary key is said to define the information in that particular table.
  • The use of foreign keys can also be used to describe the relationship between one table to another table.

The Fantastic Four: ACID

No, it isn’t related to the movie and no, it is not related to chemistry but instead ACID stands for the four important characteristics of relational databases and theta re:

A- Atomicity: Atomicity can be simply defined as ‘all or nothing’. This means all the intermediate or sub-tasks must work for any operation or transaction to happen. This ensures that the system maintains compliance with the regulations and policies. Accuracy is sustained.

C- Consistency: Consistency allows the data to remain accurate and maintain integrity. Thus, it is required for the database to remain consistent throughout any transaction. This is because the information will be updated across several applications and instances, resulting in multiple instances containing the same data.

I- Isolation: Each transaction remains independent of the other transaction through the measure of isolation. Maintaining isolation means keeping the transaction hidden and invisible until it is completed, to prevent any confusion.

D- Durability: Durability allows the user to retrieve the data in the event of a failed transaction. durability also makes sure that any data changes made will remain permanent.

Benefits of a Relational Database

  • Any kind of changes in the structure of the database will not affect the data access in any way.
  • There is higher convenience to maintaining security when compared to other database models.
  • There is no requirement to specify the entire body of database entries when they are being modified.
  • Relational databases do not require any kind of training and thus anyone can use them with little to no training.
  • A record can be applied any number of times to other tables, thus by securing accuracy one time, that particular data when reused will remain accurate. We also save time and effort by avoiding replication of the data.
  • Data retrieval is made easy by adopting various SQL techniques.

Limitations of a Relational Database

  • Due to data normalization, there will be a lot of joints in the structure that might affect the performance.
  • Semi-structured data might not be appropriate when working with relational hierarchies as they do not follow the tabular structure.
  • Thus, mapping objects can be a real tedious work when working with a relational database.
  • One cannot ensure data integrity when working with relational database systems.
  • It is difficult to work with large databases through relational database models.
  • A relational database model doesn’t allow the users to view the data storage details or the complexities of implementation.

Application of a Relational Database

  • MySQL is a management system that is open-source until its acquisition by Oracle corporation. It allows the users to enjoy in-built ACID features and can support multiple storage engines.
  • PostgreSQL is another database manager that is also free and can be sued under an open-source license. It is said to share some features with MySQLbut with higher flexibility and performance when working with huge databases due to the significant addition of Multi-Version Concurrency Control( MVCC).
  • MariaDB: Though developed as a fork of MySQL that was largely community-driven once the acquisition occurred, MariaDB remains to be open-source. MariaDB is said to run faster than MySQL through fixing limitations and additional storage engines.
  • SQLite: Unlike the previous applications, SQLite functions as more of an end application than a database manager, making it lighter and more flexible to work with a larger number of systems.

Main Differences Between Hierarchical Database and Relational database In Points

  • Hierarchical databases are first-generation data models whereas relational databases are second-generation data models.
  • Hierarchical databases were developed in 1968 by IBM whereas relational databases were developed in 1970 by E.F Codd.
  • Hierarchical database models use tree-like structures that involve a parent-child relationship between nodes whereas relational databases use the table that involves the use of attributes, tuples, primary keys, and foreign keys.
  • Hierarchical databases allow the implementation of one-to-one and one-to-many relationships whereas relational databases also allow the implementation of many-to-many relationships.
  • Data retrieval in hierarchical databases is done through sequential traversing that will search the whole tree, starting from the root node whereas the same operation in the relational database model uses SQL techniques through which, searching operations are made easy.
  • Insertion and deletion operations are very tough in hierarchical databases as a parent node cannot be deleted individually and a child node cannot be inserted without a parent node. On the other hand, both insertion and deletion operations do not have any anomaly in relational databases.
  • There are good chances that there might be inconsistency during data operation in hierarchical databases whereas there is higher consistency in relational databases due to normalization.
  • There is data independence in relational databases but not in hierarchical databases.
  • Hierarchical databases are commonly used in search engines and shopping cart applications. On the other hand, relational databases are popularly used in traditional software such as Oracle DB, IBM DB2, and many more.

Conclusion

From our discussions, we can conclude that hierarchical databases are more suitable for applications that bode well with tree structures and do not need to care about the time constraint too much whereas relational databases stand to be more appropriate for applications that work well with tables and instances i.e., operations that employ SQL techniques.

References



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"Difference Between Hierarchical Database and Relational Database." Diffzy.com, 2022. Thu. 08 Dec. 2022. <https://www.diffzy.com/article/difference-between-hierarchical-database-and-relational-database-689>.



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