What Is the Difference Between DBMS & RDBMS? (With Examples)

By Indeed Editorial Team

Published 13 September 2021

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Large companies with a massive clientele need to store, manage and study their data through a common platform. For this purpose, database management has come into the limelight over the past few decades. The quicker employees can access and modify such data, the more efficient their workflows become. Thus, DBMS and RDBMS become imperative to offer such controlled access to large sets of data. In this article, we shall read about DBMS, RDMS, their key differences and learn about DBMS a little more.

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What is DBMS?

DBMS, also known as Database Management System, is a software that serves the management and storage of data. It offers additional modification perks, such as updating, inserting or deleting data points. Moreover, it also allows creating and refining databases based on industry specifics, product types and much more. For DBMS users, software such as Microsoft Access, XML and dBase would be relevant examples.

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Four types of DBMS

To cater to the broad usability of databases, there are four types of DBMS present:

1. Hierarchical DBMS

In this DBMS type, data is represented in a top-to-bottom format, representing a tree-like structure. All the data would be related through a parent-child relationship, where each parent data point has its respective offspring data points. At the same time, each offspring comes to be under the category of a single parent.

2. Network model

This DBMS type permits the representation of more complex datasets. This includes the likes of one-to-many and many-to-many relationships between the parent and child data points. It even advocates the representation of entities in a graph format, making parts of them accessible through multiple paths. Most importantly, it allows one child data point to have a range of parent data points (multiple parents).

3. Relational model

The most universally acknowledged DBMS model, relational models work highly systematically since they normalize data in the row-column format, leading to well-structured tables. They are most often modified using SQL commands.

4. Object-oriented model

The OO model represents a range of varying data points within a singular structure, also known as an object. Each object is assigned alternating attributes, and even better, each object is eligible to create several relationships amongst them. Additionally, it also permits the storage of values and operations of data members.

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What is RDBMS? (With Examples)

RDBMS, also known as Relational Database Management System, is a much more advanced version of DBMS since it deals with data in a more structured manner. Additionally, RDBMS permits a more segmented organization of data, making access to large sets of data more convenient and resourceful. Unlike DBMS, this software manages data in the forms of rows (tuples) and columns (attributes). Since this allows data management in a tabular form, a wider range of organizations around the world have adapted to it. For RDBMS users, software such as Amazon RDS, SQL Server, MySQL, Oracle and PostgreSQL would be relevant examples.

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10 key differences between DBMS & RDBMS

While RDBMS offers a host of additional operations as compared to DBMS, it's still critical for amateur and professional software developers to understand these key differences:

  1. Storage: DBMS stores data in the form of a file, where RDBMS manages data in the form of tables. Thus, DBMS files are stored as a code file on the computer, whereas RDBMS data is stored in tables.

  2. Flexibility in users: While RDBMS allows multiple users to access a database, DBMS only permits one user. This is because DBMS is for smaller organizations that deal with a lower quantity of data, whereas RDBMS is mainly used for managing large quantities of data.

  3. Convenience in accessing data: Data in an RDBMS can easily be accessed using various available SQL queries. Moreover, several data points can be accessed simultaneously based on the application. But for DBMS, each data point needs to be individually accessed.

  4. Integrity constraints: Integrity constraints are a set of rules that allow a streamlined database modification process without negatively impacting the integrity of the data. Since integrity constraints don't function for files, DBMS doesn't support them. On the contrary, RDBMS allows integrity constraints to be implemented at a schema level.

  5. ACID (Atomicity, Consistency, Isolation, Durability): Most of RDBMS's structural perfection is attributed to its acceptance of the ACID model. Despite being tedious to create, it brings more effective data manipulation functions to the table. Whereas in DBMS, since they are old-school databases, the data cannot be stored in accordance with the ACID model. This disrupts the consistency in such databases.

  6. Redundancy occurrences: RDBMS eliminates any possibility of data redundancy because it incorporates the indexing attribute of databases. But, in the case of DBMS, because of the absence of an indexing system, data redundancy is a common affair.

  7. Security: Owing to the lack of security regulations and systems, DBMS becomes an unsafe database model for data storage. Although in RDBMS, since the software automatically instals multiple log files periodically, there is much greater security of the data.

  8. Hardware and software requirements: Since DBMS doesn't need high processing power, the need for quality hardware and software isn't a criterion to work with such software. RDBMS has capabilities and functions that work best when supported with hardware and software that can offer higher processing power.

  9. Client-server interaction: RDBMS software has always supported interactions and architectures on the client-server side, but DBMS doesn't do the same. This increases the flexibility of database applications when RDBMS-centric software is used.

  10. Access: In RDBMS, as data is stored as indexed rows and columns, extraction of the desired information becomes so much easier. This is not the case for DBMS, where data is stored using a hierarchical or navigational format.

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What is the difference between databases and DBMS?

The difference between a generic database and a DBMS is that the former simply allows users to read the data, irrespective of whether it's structured or unstructured. Usually, it's logically positioned information that is then stored on the hardware, being easy to access in a variety of manners. But, DBMS is a program or software that enables the user to interact with the database and play around with it for whatever the application may be. This could be data sorting, data removal, data manipulation and even designing basic statistical models.

Here are five key differences between databases and DBMS:

  1. Storage: A generic database can be created not only on computers but also in ledgers and other paper formats. But a DBMS is a set of data records that are strictly created, maintained and managed on a computer.

  2. Backup: In most cases, generic databases, be it an excel file or notebook, are completely wiped out in cases of system failures. But a DBMS has no possibility of data being absolutely lost, however grave the system failure is.

  3. Data access: Generic databases are curated for a few numbers (or only one) of people to handle. This limits the scope of functionality that other advanced DBMS allow. Simply put, a DBMS allows a greater number of people to study and work with the database simultaneously.

  4. Data alteration: The scope of data manipulation in generic databases is reduced due to a limitation on the amount of information that can be modified at one time. A DBMS allows large scale information manipulation since there are pre-decided functions to perform large operations in a split second.

  5. Speed: Data cannot be worked around as quickly as in generic databases as compared to a DBMS. This is attributed to the presence of SQL (Structured Query Language) in any DBMS. This availability of SQL makes information retrieval much faster and specific to the user's demands.

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Advantages of RDBMS

Though DBMS has more benefits than generic databases, it doesn't match the enhanced data management possibilities of an RDBMS. Here are few reasons why DBMS is slowly wearing away in the corporate world and RDBMS is on a consistent rise:

  • RDBMS permits exceptional feasibility for any future modifications. Above all, with regular updates, it only becomes convenient for businesses to extract valuable knowledge from their large datasets.

  • In an RDBMS, all data is normalized to a level of equality where they can be compared without facing the trouble of variances in the dataset.

  • The relational reliability within tables in an RDBMS prevents any instances of data imperfections, data isolation or compromised data integrity.

  • The key advantage is the presence of primary and foreign key concepts. This allows more than one table to be related to the other and kills the probability of data duplication. All in all, this guarantees data accuracy.

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