Relational databases are the most popular and commonly used digital databases. In this article, we discuss the relational database, how it works, examples, differences between relational and non-relational databases, and more.
What Is a Relational Database?
A relational database is a collection of data based on a model that organizes data points related to one another. The term was initially introduced by English computer scientist Edgar Frank “Ted” Codd at IBM Research Laboratory in 1970.
Relational databases organize valuable information or data into tables that can be linked to several other tables based on data common to each other. It enables users to build a new dataset from data in one or more related tables by using a single query.
The data structures used by relational databases include tables, indexes, and views. The major components of a relational database are tables, columns, and rows.
A relational database management system (RDBMS) is used to maintain relational databases. Moreover, many RDBMSs support structured query language (SQL) for querying and management.
Read more: SQL Query Optimization Best Practices
How Does a Relational Database Work?
Relational databases work by linking information or data from multiple related tables through “keys.” Keys are the unique identifiers that can be assigned to a row of unique data contained within a table. This unique identifier is known as a “primary key,” and may include IDs, serial numbers, user names, etc.
The primary key can be included in a record at another table when the record has a relation to the primary record in the main table. If a primary key is added to the record in another table, it is known as a “foreign key.” The connection between primary and foreign keys creates a relationship between datasets in multiple tables.
Relational Database Examples
The most popular standard relational databases include:
- Microsoft SQL Server
- IBM Db2
The most commonly used cloud-based relational databases include:
- Oracle Cloud
- AWS Relational Database Service
- Google Cloud SQL
- IBM Db2 on Cloud
- SQL Azure
Relational vs Non-Relational Database: What Is the Difference?
Relational databases are developed for structured data that conforms to a predefined data model. Conversely, non-relational databases are used for unstructured data. For example, one would use a relational database for sales tracking, billing, or asset management.
Non-relational databases tend to have more specific use cases. An example of a non-relational database use case would be working with big data that requires highly optimized search indices.
The differences between the relational and non-relational databases are given below.
|SQL and others
|Amounts of data
|Varies, some can support big data
|Best suited to
|Heavy, structured data transactions
|Specialized use cases
|Oracle, MySQL, PostgreSQL
|MongoDB, Dynamo DB, Redis
Relational Database Model
Relational database models represent a database as a gathering of relations and relation sets. Relations are the table of related data values, where every row represents a collection of data values and denotes a relationship or real-world entity. The table and its columns are used to interpret the values in each row.
In the relational database model, information or data is stored as tables. Note that the physical storage of the related data is independent from the way it is logically organized.
Types of Relationships Between Entities
The association between two entities is referred to as a relationship. There are three types of relationships between two entities in relational database design.
- One-to-One relationship
- One-to-Many or Many-to-One relationship
- Many-to-Many relationship
In the One-to-One relationship, each record in Table X relates to one, and only one, record in Table Y, and each record in Table Y relates to one, and only one, record in Table X. For example, the relationships between an employee and their company laptop.
In the One-to-Many or Many-to-One relationship, each record in Table X relates to many records in Table Y, and each record in Table Y relates to many records in Table X. For example, the relationships between a company and its stock of employee laptops.
In the Many-to-Many relationship, many records in Table X relate to many records in Table Y, and many records in Table Y relate to many records in Table X. For example, the relationships between company laptops and their installed applications.
Relational databases offer users and businesses a better understanding of the relationships between available information and data. Over the years, relational databases have successfully managed large amounts of data and have gotten better, faster, stronger, and easier to work with — which is why they remain the most popular type of database.