What is a Relational Database? Examples and Applications

Relational databases are crucial for organizing and managing data. They store data in interconnected tables, making it easier to retrieve information quickly. For example, a relational database for customers might have tables for 'Name,' 'Email,' and 'Phone Number.'

Though they may seem simple, relational databases have been streamlining data organization for decades. Let’s dive into the world of relational databases, examine a few examples, and explore their numerous uses.

What is a Relational Database?

arranges data into structured tables consisting of rows and columns. Each table is dedicated to a specific category, such as customers, products, or transactions. The rows represent individual entries, and the columns contain data attributes like names, dates, or amounts. These tables are connected through keys, which enable the linking and retrieval of related data.

The term 'relational' refers to the ability to connect or link data from different tables. A primary key acts as a unique identifier within a table, which is connected to a foreign key in another table. This relationship ensures that related data can be easily identified and accessed.

History of the Relational Database

Databases have been integral to business computing since the dawn of the digital age. The relational database itself was introduced in 1970, when E.F. Codd, a researcher at IBM, published a paper explaining the concept. Since then, relational databases have become widely used and are now the standard for data management.

In the past, databases were flat. This meant that data was stored in a single long text file, referred to as a tab-delimited file. Entries in this file were separated by a special character, like a vertical bar (|). Each entry contained several details (fields) about an object or person, organized together into a record. Searching for specific information or generating reports with selected fields from each record was quite challenging with this structure. Here’s an example of a file from 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

As you can see, to gather related details such as age or salary, you'd need to go through the entire file sequentially. In contrast, a relational database allows for easy searching and quick retrieval of specific data. It also makes it simple to sort by any field and generate reports featuring selected fields from each record. Relational databases store data in tables, where columns represent the fields and rows represent individual records.

How Relational Databases Work

Relational databases enable quick comparisons of data by organizing it into columns. This structure allows the creation of entirely new tables from existing ones, by utilizing the relationships between similar data. Essentially, it leverages the connections within the data to boost the speed and flexibility of the database.

The term 'relational' is derived from mathematical relations. A typical relational database consists of anywhere between 10 and over 1,000 tables. Each table contains one or more columns that other tables can reference, allowing them to pull data from those tables.

By storing information in a separate table, the database can generate a compact table with locations, which can then be accessed by other tables for various purposes. In a large database, such as the one used by a major website like Amazon, hundreds or even thousands of interconnected tables work together to quickly retrieve specific data when needed.

Relational databases are constructed using a specialized computer language called Structured Query Language (SQL), which is the industry standard for database communication. SQL serves as the foundation for all major database applications available today, including Access and Oracle.

Examples of Relational Databases

Numerous relational databases are in wide use today, each offering its own unique set of features. Let’s explore some of the most popular examples:

How They Compare To Non Relational Databases

Non-relational databases, also known as NoSQL, provide the flexibility to manage unstructured or semi-structured data. These databases are particularly useful in situations where scalability and speed are more important than enforcing strict data consistency. Examples include document stores like MongoDB, key-value stores like Redis, and column-family stores like Cassandra.

These systems support horizontal scaling, allowing them to function across distributed environments, making them well-suited for applications that handle large amounts of data, such as real-time analytics or content management systems. Additionally, NoSQL databases offer schema flexibility, allowing for dynamic data structure changes without needing migration or downtime.

Benefits of a Relational Database System

The relational data model excels in handling multiple tables and storing vast amounts of data. It brings numerous benefits, making it a preferred choice for many applications:

Challenges of Using Relational Database Systems

While relational databases are highly effective, they also come with certain challenges. One of the key difficulties is their complexity, as setting them up and managing them requires specialized expertise. Proficiency in SQL and database design is crucial to ensure that the system runs smoothly and efficiently.

Another challenge is that large relational databases are resource-heavy, demanding considerable computing power to maintain. As the amount of data increases, businesses may need to invest in more powerful servers or cloud-based storage solutions to handle the growing demands.

Relational databases are not well-suited for handling unstructured data, such as videos or social media content, which do not align well with the table-based structure. In such cases, alternative database models might be more effective.

Learn More Today

Relational databases are vital in organizing unstructured data in today’s world. Whether you are overseeing a small project or managing a large business, mastering relational databases can greatly enhance your ability to manage information effectively.

Despite their challenges, the advantages of relational databases in maintaining data integrity, ensuring security, and providing flexibility make them essential tools across numerous industries. If you're aiming to optimize your data handling, a relational database could be the key solution.