Ultimate Guide to Relational Databases

29 Oct · 6 min read

Ultimate Guide to Relational Databases

A database is present in every program. It is the place where you keep all of the data that your software needs to run. In this article, we'll have a closer look at a relational database, which is one of the most common types of databases. Before we dive deep into an understanding relational database, let’s get familiar with the definition of a database. 

A database is an organized collection of data that is easy to access and manage simultaneously. Data gets saved differently depending on the application and the method followed to store data proves to be the key parameter impacting the performance of the individual operations such as modification, deletion, reading, and writing. 

There are various types of databases followed by the most prominent one among them is the Relational Database. 

What is a Relational Database?

The term ‘relational database’ was first proposed by E. F. Codd in 1970.  

In a relational database, the data is stored in linear files termed as “relations” or “tables” in the form of rows and columns. 

The introduction of SQL (Structured Query Language) was proposed by the relational model which is used to access and modify data in databases. 

Basics of Relational Database Implementation

Databases support different versions of SQL followed by their distinct implementations. Although the SQL language is defined by a specific standard, there are some significant versions between the SQL supported by different databases. These distinct versions are often termed as ‘Dialects’ 

Below is a list of the most commonly used Relational Database Implementations: 

  • Oracle
  • SQL Server
  • PostgreSQL
  • SQLite
  • HyperSQL
  • MySQL

A query is the fundamental operating unit of SQL. There are three different forms of data search queries which are as follows: 

  • Projection (Choosing the subset of fields, columns, features)
  • Selection (Selection of records/rows based on specified criteria)
  • Joining (Merging data from multiple tables)

Query pattern is shown in the image below: 

Advantages of Relational Database

The key advantages of Relational Database are: 

  • Categorization of Data
  • Enhanced Security
  • Guaranteed Accuracy
  • Ease of use
  • Collaboration

Even though Relational Database has been there since the 1970s, the advantages of the Relational Database have undoubtedly made it the widely used database model. 

Rules for Relational Database

The essential rules for Relational Databases are as follows: 

  1. Common data types are used to represent every data value.
  1. Each data is presented in the form of two-dimensional tables termed “relations”.
  1. Each table has one or more columns called attributes and zero or more rows called tuples. Each row is made up of columns that are evenly spread and filled with values that change from one row to another row.
  1. Once the addition of data takes place in the database, it becomes feasible to compare values from different columns and merge them with matching rows from distinct tables.

This enables room for data binding while performing other complex operations across the database. All the operations performed are logical regardless of the positioning of rows. Moreover, Rows can be stored in any order irrespective of their order of placement. 

Types of Relations:


A one-to-one relationship occurs when one record in a table matches with at least one record from another table. 


A one-to-many relationship occurs when one record in a table can be associated with one or more records in another table. 


A many-to-many relationship is likely to occur when multiple records in one table are associated with multiple records in another table. 

There can be one or more unique columns within the table used to locate the specific row as the row cannot be identified by its position. 

The columns are termed as “Primary Key” of the table. 

Note: A table might not always contain a primary key in all the tables. It can contain a foreign key which is defined as the primary key from different tables linking the two tables together. 

5. Normalization of Data

Normalization is the process of organizing data so that it flows smoothly in and around the database. 

In a relational database, the rules for organizing data are termed as “normal forms” involving rules that can prove to be a benchmark resulting in the consistency of data. 

Disadvantages of Relational Database

Older Technology

Since the relational database has been proposed quite a while ago, developers consider it outdated and often prefer to use modern alternatives. 

Structural Overhead

A certain structure has been followed underlying the relational model ensuring the integrity of data but there are certain obstacles that arise when it comes to performing simple operations. Therefore, one needs to adopt modern solutions resulting in the flexibility of data. 

Lack of Scalability

In a large project, maintaining a relational database can become extremely expensive and challenging such as Facebook or any big enterprise data application. Due to compatibility issues of modern types of software with relational databases, there have been many alternatives that have been developed as a replacement. 

Use of Relational model and SQL Language can be Tricky

One of the major complaints with the Relational model and SQL Language is to maintain their precision throughout the task. Thus, not qualifying to be the first choice for developers. 

Alternatives to Relational Databases-Modern Database models

Due to the reliability of relational databases on SQL, its equivalent is termed as NoSQL. 

The key feature of NoSQL databases is that they are non-relational. 

There are four types of NoSQL Databases: 

  • Key-Value Stores
  • Document-Stores
  • Graph-Stores
  • Column Stores


To conclude, the usage of databases in modern businesses is not just limited to storing and processing data as it is further used for analyzing as well. Organizations can use the stored data to operate more efficiently, make better decisions, improve flexibility and scalability using databases and other processing and business intelligence technologies. Therefore, choosing the appropriate data model is an essential decision when it comes to the creation of a database project. 

Please feel free to contact us for further information on making the right choice for the data model and we would be happy to help you! 

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