Relational Database Management System (RDBMS) provides a foundation for numerous apps and services in an enterprise. Technologically, RDBMS is considered ancient. However, the solid theoretical foundation of relational database technology has kept it pertinent in a volatile industry.
This is why even non-relational databases to store information include RDBMS-like features, such as the SQL interface in Hadoop. Some popular examples of relational database management systems include Microsoft SQL Server and MySQL, which may store employee records, customer records, and other business information.
- What is a Database Management System?
- What is a Relational Database Management System?
- Differences between RDBMS and DBMS
- How does an RDBMS work?
- Advantages of RDBMS
What is a Database Management System?
A database management system (DBMS) is software designed to store, retrieve, and manage data. The most prevalent DBMS in an enterprise database system is the RDBMS. The complete form of RDBMS is Relational Database Management System. Now that it is clear what a database management system is, let’s learn about the relational database management system.
What is Relational Database Management System with Example?
According to E. F. Codd’s relational model, an RDBMS allows users to construct, update, manage, and interact with a relational database, allowing storing data in a tabular form. Therefore, consider RDBMS as an advanced data management system that makes gaining insights from data a lot easier. But why do we need a relational database?
Today, various businesses use relational database architecture instead of flat files or hierarchical databases for their company database management system (DBMS). So, what is the reason for creating a relational database? A relational database is purpose-built to efficiently handle a wide range of data formats and process queries. And how is data in a relational database management system organized?
The answer to this is simple: a relational database management system organizes data in tables that can be linked internally depending on shared data. This allows a user to retrieve one or more tables with just one query easily. On the other hand, flat-file stores data in a single table structure, which is less efficient and consumes more space and memory.
Hence, we need a relational database. An example of a relational database management system could be a production department in an organization that leverages this model to process purchases and track inventory.
The most commercially available and company-wide database management system or relational database management system in use today is Structured Query Language (SQL database) to access the database.
Other widely used relational database management systems for companies include Oracle database, MySQL, PostgreSQL (an open-source relational database), and Microsoft SQL Server. RDBMS structures are commonly used to perform four basic operations: CRUD (create, read, update and delete), which are critical in supporting consistent data management.
Now that you know the definition of an RDBMS let’s look at how it differs from a DBMS and the characteristics of a relational database system.
Differences Between RDBMS and DBMS
There are some contrasting differences between RDBMS vs. DBMS. An RDBMS is an advanced version of a DBMS. Unlike a DBMS that manages databases on a computer network and hard disks, an RDBMS database helps maintain relationships between its tables.
Here are some of the main differences between an RDBMS and a DBMS:
- Number of operators: A DBMS allows only a single operator simultaneously, whereas multiple users can operate an RDBMS concurrently. An RDBMS uses intricate algorithms that enable several users to access the database while preserving data integrity simultaneously, significantly reducing response time.
- Hardware and software need: A DBMS utilizes fewer data storage and retrieval resources than an RDBMS. The latter is more complex due to its multi-table structure and cross-referencing capability, making it costlier than a DBMS. RDBMSs are also generally used for enterprise-class applications, while DBMSs are more commonly utilized for smaller, purpose-specific applications.
- Data modification: Altering data in a DBMS is quite difficult, whereas you can easily modify data in an RDBMS using an SQL query. Thus, programmers can change/access multiple data elements simultaneously. This is one of the reasons why an RDBMS is more efficient than a DBMS.
- Data volume: A DBMS is more suitable for handling low data volume, whereas an RDBMS can handle even large data volumes.
- Keys and Indexes: A DBMS doesn’t involve keys and indexes, whereas an RDBMS specifies a relationship between data elements via keys and indexes.
- Data consistency: As a DBMS does not follow the ACID (Atomicity, Consistency, Isolation, and Durability) model, the data stored can have inconsistencies. In contrast, an RDBMS follows the ACID model, making it structured and consistent.
- Database structure: A DBMS works by storing data in a hierarchical structure, while an RDBMS stores data in tables.
- Data fetching speed: In a DBMS, the process is relatively slow, especially when data is complex and extensive. This is because each of the data elements must be fetched individually. In an RDBMS, data is fetched faster because of the relational approach. Plus, SQL facilitates quicker data retrieval in an RDBMS.
- Distributed databases: A DBMS doesn’t support distributed databases, whereas an RDBMS offers full support for distributed databases.
- Client-server architecture: Unlike a DBMS, an RDBMS supports client-server architecture.
How Does an RDBMS Work?
Data is stored in a relational database in the form of multiple tables. A key question here arises, how does a database structure work, and how is it implemented? Let’s understand this in detail.
A database structure works by arranging every table into rows (known as records/ tuples) and columns (known as fields/attributes). Tables, columns, and rows are the three major components of a relational database.
Here is an example of a type of business database to process customers’ orders. In this type of database, the first column contains customer ID, which is the primary key. The primary key is used to identify each unique record in a table. Each column (or attribute) stores bits of information, and the database assigns a unique customer ID to each row.
The data structure used to implement a relational database is as follows:
As seen in the example above, the data structure of a single table. While most commonly, data is more complex and is stored in multiple tables. The tables are then connected based on pre-existing relationships.
The tables can be connected in different ways, such as:
- A record in one table could be related to another record in a different table (1:1 relationship)
- A record in one table may be related to several records in other tables (1:M relationship)
- Several table records could be linked to multiple records in a different table (M: N relationship)
However, before tables are created, a relational database management system must ensure that:
- Each table has a unique primary key, which has no null values.
- The foreign key, which is used to relate to 2 tables, is preserved in one table and refers to the primary key of another table.
- No column has a null value (empty cell).
An RDBMS usually comes with data dictionaries and collections of metadata, which are beneficial in data management. A data dictionary defines the data objects of every user within the database. As a result, it helps users identify all the objects that exist in the database and who can access them.
For instance, it’s humanly impossible to remember all the tables stored in a huge database. If you want to search for a specific table, such as Products, you can use a data dictionary to look up all the tables named Products. Then, you can identify your required one from the list of tables.
Advantages of RDBMS
The pros of a relational database management system offer a systematic view of data, which helps businesses improve their decision-making processes by enhancing different areas.
Various other advantages of a relational database model:
Enhanced Data Security
The authorization and access control features in relational database software support advanced encryption and decryption, enabling database administrators to manage access to the stored data. This offers significant benefits in terms of security. In addition, operators can modify access to the database tables and even limit the available data to others. This makes RDBMSs an ideal data storage solution for businesses where the higher management needs to control data access for workers and clients.
Retain Data Consistency
It is easier to add new data or modify existing tables in an RDBMS while maintaining data consistency with the existing format. This is mainly because an RDBMS is ACID-compliant.
Better Flexibility and Scalability
An RDBMS offers more flexibility when updating data as the modifications only have to be made once. For instance, updating the details in the main table will automatically update the relevant files and save you the trouble of changing several files one by one. Plus, each table can be altered independently without disturbing the others. This makes relational databases scalable for growing data volumes.
Relational databases are considered low-maintenance because users can quickly test, regulate, fix and back up data as the automation tool in RDBMS help systematize these tasks.
Reduced Risk of Errors
In relational database software, you can easily check for errors against the data in different records. Furthermore, as each data item is stored at a single location, there’s no possibility of older versions blurring the picture.
Over time, RDBMSs have evolved to provide increasingly advanced query optimization and sophisticated plugins for enterprise developers. As a result, various enterprise applications of relational database management systems exist. They also serve as a focal point in numerous applications, such as reporting, analytics, and data warehousing.