What Is a Relational Database? Example and Uses

organizes data into tables with rows and columns. Each table focuses on a specific subject, like customers, products, or orders. The rows represent individual records, while the columns store data attributes like names, dates, or quantities. These tables are linked using keys, which allows different pieces of data to connect and be accessed together.

The term "relational" comes from the fact that data in different tables can be linked or related. A primary key is a unique identifier in each table that connects to a foreign key in another table. This relationship ensures that information can be easily matched and retrieved.

Databases have been a staple of business computing from the very beginning of the digital era. In fact, the relational database was born in 1970 when E.F. Codd, a researcher at IBM, wrote a paper outlining the process. Since then, relational databases have grown in popularity to become the standard.

Originally, databases were flat. This means that the information was stored in one long text file, called a tab delimited file. Each entry in the tab delimited file is separated by a special character, such as a vertical bar (|). Each entry contains multiple pieces of information (fields) about a particular object or person grouped together as a record. The text file makes it difficult to search for specific information or to create reports that include only certain fields from each record. Here's an example of the file created by a flat database:

Lname, FName, Age, Salary|Smith, John, 35, $280|Doe, Jane, 28, $325|Brown, Scott, 41, $265|Howard, Shemp, 48, $359|Taylor, Tom, 22, $250

You can see that you have to search sequentially through the entire file to gather related information, such as age or salary. A relational database allows you to easily find specific information. It also allows you to sort based on any field and generate reports that contain only certain fields from each record. Relational databases use tables to store information. The standard fields and records are represented as columns (fields) and rows (records) in a table.

With a relational database, you can quickly compare information because of the arrangement of data in columns. The relational database model takes advantage of this uniformity to build completely new tables out of required information from existing tables. In other words, it uses the relationship of similar data to increase the speed and versatility of the database.

The "relational" part of the name comes into play because of mathematical relations. A typical relational database has anywhere from 10 to more than 1,000 tables. Each table contains a column or columns that other tables can key on to gather information from that table.

By storing this information in another table, the database can create a single small table with the locations that can then be used for a variety of purposes by other tables in the database. A typical large database, like the one a big website like Amazon would have, will contain hundreds or thousands of tables like this all used together to quickly find the exact information needed at any given time.

Relational databases are created using a special computer language, structured query language (SQL), that is the standard for database interoperability. SQL is the foundation for all of the popular database applications available today, from Access to Oracle.

Several relational databases are widely used today, and each offers its own set of features. Let’s look at some popular examples:

Non-relational databases, often referred to as NoSQL databases, offer flexibility for handling unstructured or semi-structured data. These databases excel in scenarios where scalability and speed are more critical than strict data consistency. Common types include document stores like MongoDB, key-value stores like Redis, and column-family stores like Cassandra.

These systems allow for horizontal scaling across distributed environments, making them ideal for applications that need to handle large volumes of data, such as real-time analytics or content management systems. Additionally, NoSQL databases provide schema flexibility, enabling dynamic changes in data structure without the need for migration or downtime.

Proficient at managing multiple tables and storing data, the relational data model offers several key advantages:

Relational databases, while powerful, do present several challenges. One of the main difficulties is their complexity, as setting up and managing these databases often requires specialized knowledge. Understanding SQL and database design is essential to ensure the system operates efficiently.

Another challenge is that large databases are resource-intensive, requiring substantial computing power to maintain. As data grows, businesses may need to invest in more robust servers or cloud storage solutions to handle the increased load.

Additionally, relational databases are not ideal for unstructured data, such as videos or social media posts, which do not fit neatly into tables. In such cases, other types of databases may be more appropriate.

Relational databases play a crucial role in making sense of unstructured data in today’s world. Whether you’re managing a small project or a large-scale enterprise, understanding how relational databases work can help you manage your information better.

While they do come with challenges, their benefits in ensuring data integrity, security, and flexibility make them an invaluable tool for countless industries. If you’re looking to improve how you handle data, a relational database might be the solution you need.

This article was updated in conjunction with AI technology, then fact-checked and edited by a HowStuffWorks editor.