What is a Relational Database?

• Relational Database Definition

  Relational Database Definition

  A relational database is also known as a digital database that stores and provides information in a tabular format. This model was proposed in 1970 by E. F. Codd. A relational database allows you to easily find, scan, and sort specific information based on the relationship among the different fields defined within a table.
  
• How is data in a relational database system organized?

  How is data in a relational database system organized?

  A relational database is a collection of data items with predefined relationships. These data items or business-critical information are organized in columns and rows. Tables consist of information about objects, columns within tables include a field, and a field consists of the actual value of an attribute. On the other hand, the rows consist of a collection of related values of one object or entity. Moreover, the rows can also be marked with a unique identifier called a primary key. The data within these tables can be accessed in multiple ways. Relational databases allow users to access information without reorganizing the tables. The role of the unique identifier is to identify the information in the table.

  What is an RDBMS?

  A relational database management system (RDBMS) is a set of programs enabling IT administrators to create, update, and interact with a relational database. An RDBMS uses Structured Query Language (SQL) to access the database and its information. They’re some of the most popular databases worldwide and offer ease and flexibility for organizing large amounts of data with quick implementation and high performance.

  Advantages of using an RDBMS

  One of the significant benefits of using a relational database is it allows users to organize data in an appropriate manner they can easily access anytime, anywhere. This arrangement can also be made simpler using queries and filters.

  A relational database management system offers several benefits over any other type of database:

  • Simplistic model: An RDBMS is one of the simplest models, and organizations often prefer using them when it comes to storing vast quantities of business-critical data. They don’t involve any complex structuring or querying processes like hierarchical database structuring. This can be handled using simple SQL queries.
  • Data accuracy: Accuracy is one of the significant advantages of using an RDBMS. They include multiple tables with rows related to each other with foreign key concepts. This makes the data non-repetitive and eliminates the chances of data duplication.
  • Easy access to data: RDBMSs don’t follow a specific or complex pattern, unlike other databases where the data and information is accessible only by navigating through a hierarchical or tree-like model. Authorized users can access the data by querying any table in the relational database. Users can add relational tables to simplify querying data in several different ways, like join queries and conditional statements. Moreover, they can modify the data based on the values from the tables, which can be incorporated in the outcome. A relational database allows users to fetch data in the easiest way possible.
  • Data integrity: An RDBMS consists of a crucial characteristic known as data integrity. Validations and authentic entries of data ensure the overall organization of data into tables, columns, and rows makes it suitable for creating relationships. The data reliability in these databases makes the data reliable, perfect, and easily accessible.
  • Flexibility: A relational database can expand and scale with a flexible structure to accommodate the constantly shifting requirements. This helps update, delete, and store incoming data in huge quantities. Users can insert, edit, delete, add tables, columns, and rows in the database to meet business needs. An RDBMS can hold an infinite number of rows, columns, and tables; however, it restricts the transformation and development of data or values. Only authorized users can alter the data.
  • Normalization: Normalization refers to the process of organizing data in a database in tables, columns, and rows. It also includes establishing relationships between tables and entities to protect data and make databases more flexible by eliminating redundancy. The normalization process provides a set of characteristics and regulations for creating and evaluating database structure and the relational database model. It offers reassurance the database is reliable, scalable, and flexible.
  • High security: Relational databases allow users to tag some tables as confidential to ensure their business-critical data is secure. In a relational database, users can set boundaries, such as login credentials, and authorize specific users for their level of information access.
• Relational vs. non-relational database

  Relational vs. non-relational database

  Relational database:

  A relational database, also known as a SQL database, separates data in tables, rows, and columns, also referred to as records. In this type of database, the information is linked within multiple tables to make it easier for users to search, find, and scan through specific information. One of the significant advantages of this type of database is referential integrity, which refers to the accuracy and consistency of data.

  Non-relational database:

  A non-relational database is also known as a NoSQL database, and it stores data in an unstructured format. Unlike relational databases, the data is not explicitly arranged into tables, rows, and columns in NoSQL. Instead, a storage model is used to optimize specific requirements depending on the information in this database. Some of the most popular NoSQL databases are MongoDB and Redis.
• Relational database examples

  Relational database examples

  Some of the most popular RDBMSs include Microsoft SQL Server, Oracle Database, MySQL, and IBM DB2. Among these, cloud-based relational databases are widely used, as they enable companies to outsource various processes, such as database maintenance, infrastructure support requirements, patching, and more. Examples of cloud relational databases include Google Cloud SQL, SQL Azure, Oracle Cloud, and Amazon Relational Database Service.