What Is A Relational Database (RDBMS)?  |  Google Cloud (2024)

Developed by E.F. Codd from IBM in the 1970s, the relational database model allows any table to be related to another table using a common attribute. Instead of using hierarchical structures to organize data, Codd proposed a shift to using a data model where data is stored, accessed, and related in tables without reorganizing the tables that contain them.

Think of the relational database as a collection of spreadsheet files that help businesses organize, manage, and relate data. In the relational database model, each “spreadsheet” is a table that stores information, represented as columns (attributes) and rows (records or tuples).

Attributes (columns) specify a data type, and each record (or row) contains the value of that specific data type. All tables in a relational database have an attribute known as the primary key, which is a unique identifier of a row, and each row can be used to create a relationship between different tables using a foreign key—a reference to a primary key of another existing table.

Let’s take a look at how the relational database model works in practice:

Say you have a Customer table and an Order table.

The Customer table contains data about the customer:

• Customer ID (primary key)
• Customer name
• Billing address
• Shipping address

In the Customer table, the customer ID is a primary key that uniquely identifies who the customer is in the relational database. No other customer would have the same Customer ID.

The Order table contains transactional information about an order:

• Order ID (primary key)
• Customer ID (foreign key)
• Order date
• Shipping date
• Order status

Here, the primary key to identify a specific order is the Order ID. You can connect a customer with an order by using a foreign key to link the customer ID from the Customer table.

The two tables are now related based on the shared customer ID, which means you can query both tables to create formal reports or use the data for other applications. For instance, a retail branch manager could generate a report about all customers who made a purchase on a specific date or figure out which customers had orders that had a delayed delivery date in the last month.

The above explanation is meant to be simple. But relational databases also excel at showing very complex relationships between data, allowing you to reference data in more tables as long as the data conforms to the predefined relational schema of your database.

As the data is organized as pre-defined relationships, you can query the data declaratively. A declarative query is a way to define what you want to extract from the system without expressing how the system should compute the result. This is at the heart of a relational system as opposed to other systems.

Now that you understand how relational databases work, you can begin to learn about the many relational database management systems that use the relational database model. A relational database management system (RDBMS) is a program used to create, update, and manage relational databases. Some of the most well-known RDBMSs include MySQL, PostgreSQL, MariaDB, Microsoft SQL Server, and Oracle Database.

Cloud-based relational databases like Cloud SQL, Cloud Spanner and AlloyDB have become increasingly popular as they offer managed services for database maintenance, patching, capacity management, provisioning and infrastructure support.

Ready to get started? Create a 90-day Cloud Spanner free trial instance with 10 GB of storage at no cost.

The main difference between relational and non-relational databases (NoSQL databases) is how data is stored and organized. Non-relational databases do not store data in a rule-based, tabular way. Instead, they store data as individual, unconnected files and can be used for complex, unstructured data types, such as documents or rich media files.

Unlike relational databases, NoSQL databases follow a flexible data model, making them ideal for storing data that changes frequently or for applications that handle diverse types of data.