Simplifying relational databases: A comprehensive guide

What differentiates modern spreadsheets from any other table?

Let me answer: the fact that the values in the cells, rows, and columns are all in relation with each other – if you set it up right.

So, what do we get if we increase the relation between each data that is inside a table, taking it even further than Excel? We get Relational databases. Some people call it “rational databases” but no, it’s “relational databases”. For example, MySQL is a relational database – if that makes things a bit clearer for you.

Other than that, in this article, we will define relational databases, give relational database examples, and dive deep into relational database components. So, without further ado, let’s get started:

Table of contents

• What is a relational database?
• Components of relational databases  
• How relational databases are structured
• Benefits of using relational databases  
• Relationships in relational databases  
• Examples of relational databases  
• Relational vs. non-relational databases  
• Conclusion
• Frequently asked questions

What is a relational database?

A relational database is like a digital filing system where data is organized into tables with rows and columns. What makes it unique is its ability to establish connections between different pieces of data using keys.

Let me expand the definition a bit. W-What sets relational databases apart is their ability to establish connections between different pieces of data.

This is where the term "relational" comes into play.

Instead of storing data in isolation, relational databases allow you to link related information across multiple tables using keys—unique identifiers that establish relationships between records.

For example, think of a customer database for an online store. You might have separate tables for customers, orders, and products.

By using keys, you can link each order to the corresponding customer and product, creating a web of interconnected data.

This interconnectedness is crucial because it enables powerful functionalities like data integrity, where changes made to one piece of information automatically propagate throughout the database. For instance, if a customer updates their address, that change reflects in all their past and future orders without manual intervention.

Furthermore, relational databases provide flexibility in how you view and interact with your data. You can query the database using languages like SQL to retrieve specific information, generate reports, or perform complex analyses.

Additionally, modern tools like Retable offer intuitive interfaces that allow users to work with databases without needing to write code.

So, we talked about tables, records, keys, fields... What is a field in a database, even?

Components of relational databases

The components of a relational database are:

1. Tables: These are the main building blocks, representing individual datasets, each composed of records and fields. On the surface, a relational database table isn’t much different from any table, but on the backend, they are.  

2. Records: They are unique inputs stored in tables, just like rows in a spreadsheet.

3. Fields: These represent characteristics of the subjects in the relational database table, like columns in a spreadsheet.

4. Keys: Special fields that establish relationships between records across multiple tables, including primary keys (unique identifiers for each record) and foreign keys (pointers to primary keys in other tables). You can also think of keys as cell identifiers.

5. Table relationships: Describes how tables share information, including one-to-one, one-to-many, and many-to-many relationships. We will dig deeper into the relationships below.

6. Database schema: A blueprint defining the structure of the database, including rules for data types and relationships between tables. These rules can be a “select one of 3 options” or “this column can only include numbers”, so, nothing fancy really.

Let’s make all those terms easier to understand with an example and a breakdown of each component:

How relational databases are structured

Let’s work with an example relational database from here on. This relational table below was made with Retable – a modern and no-code relational database management system.

Looks like just a table, right? Well, it can do more than just showing you different input values. All those cells are interconnected and have different sets of rules.

Let me explain further:

Relational tables vs. relational database schemas

A relational database table without a schema would be just a table with a fancy name. The schema puts all the data in order with rules.

Let me visualize it for you with a screenshot of Retable:

See all those customizable rules? That is the modern way to set up a relational database schema without a single line of code. All the limitations you set to a certain row change how all the data interacts with each other. And the combination and relation of all those rules are called the “relational table schema”.

Benefits of using relational databases

Each field in a database represents a specific piece of data related to the subject of the table. For example, if you have a table for storing information about customers, the fields might include their name, email address, phone number, and so on.

Using a relational database makes this storing of data easier because:

• Organizes data: Helps structure the information stored in the database, making it easier to manage and retrieve.
• Ensures data integrity: By specifying the type of data allowed in each field (e.g., text, numbers, dates), it helps maintain consistency and accuracy of the stored data.
• Facilitates data manipulation: Enables performing various operations such as filtering, sorting, and querying the data effectively.
• Supports relationships: Fields play a crucial role in establishing relationships between tables through primary and foreign keys, thus enabling the database to maintain relational integrity.

Relationships in relational databases

So, we have been talking about the fact that the interconnectedness of values is what makes a relational database different from any other table that you create on word.

So, what are these connections? How do values connect with one another and what are the different connections between relations in those databases?

Establishing connections between tables

A superior advantage of relational databases is that you can establish connections within them, and between them. If you are accustomed to Excel and other spreadsheet types, you might know that importing dynamic data between tables isn’t that difficult. And this is just like that.

By connecting the schema of two relational database tables with a rule, you can establish connections between different tables.

And that kind of relationship doesn’t have to be a one-value-just-to-another kind of connection. Let’s discover the possibilities:

Types of table relationships

One-to-one relationships

In a one-to-one relationship, each record in one table is associated with exactly one record in another table, and vice versa.

It's like a direct link between two entities where each entity has a unique counterpart in the other table.

An example could be a relationship between a person and their passport information. Each person has exactly one passport, and each passport belongs to exactly one person.

One-to-many relationships

In a one-to-many relationship, each record in one table can be associated with one or more records in another table, but each record in the second table is associated with only one record in the first table.

This is a common type of relationship where one entity has multiple related entities in another table.

For example, a customer may have multiple orders in an e-commerce system. Each order belongs to exactly one customer, but a customer can have many orders.

Many-to-many relationships

In a many-to-many relationship, each record in one table can be associated with one or more records in another table, and vice versa.

This type of relationship is more complex and typically requires a junction table to manage the associations between the two tables.

For example, in a school database, students may enroll in multiple courses, and each course may have multiple students enrolled. This creates a many-to-many relationship between students and courses.

Relational database examples

Let’s take a look at a relational database example and list out each of its components to fully visualize the concept:

1. Tables: There are 2 tables in this relational database: Table 1 and Table 2. You can switch between one another from the top right.

2. Records: Each input in a single row is an input for each table.

3. Keys: The rows are the keys. Notice how each row has a different rule and a different purpose? You can also see that the table highlights errors if the input value doesn’t match the rule of the key on row 5.

4. Table relationships: The two tables are interconnected with a one-to-one relationship rule. The first column on the second table imports data from the first table, and the second row on the second table imports the corresponding data from the first table. Also, the third column attributes a unique identifier to each row.

5. Database schema: There are a lot of set rules for each column. For instance, you can see that only one option can be selected for column 4 in table 1. Also, columns 2 and 3 only accept numbers as valid inputs.

Relational vs. non-relational databases

• Relational databases organize data into tables, where each table represents a specific type of information, like customers, products, or orders.

Within these tables, data is structured into rows (also called records) and columns (also called fields). Each row represents a single instance of the data type, while each column represents a specific attribute or characteristic of that data.

The key concept in relational databases is the relationship between tables. Through primary and foreign keys, tables can be linked together, allowing for complex queries and analyses across different datasets.

Think of it like organizing information in a spreadsheet but with the added ability to link related data together, creating a more interconnected and efficient system for managing large amounts of information.

• However, non-relational databases, also known as NoSQL databases, take a different approach to storing data than relational databases.

Instead of using tables, rows, and columns, non-relational databases often use different data models like key-value stores, document stores, or graph databases.

These databases are more flexible and scalable, making them suitable for handling large volumes of unstructured or semi-structured data, such as social media posts, sensor data, or real-time analytics.

⭐ In short, while relational databases excel at maintaining strict data integrity and enforcing relationships between tables, non-relational databases prioritize performance, scalability, and flexibility, making them ideal for certain use cases where data structure may evolve rapidly or be less predictable.

Conclusion

While the name sounds fancy, relational databases are not complicated matters. Well, they used to be, while the only available relational database management system was SQL.

Now, you don’t need to know a single line of code to track and manage your data in a relational database system.

Start your journey with Retable right now and get a 20% discount with the code “WELCOMEFAM20”!

Frequently asked questions

Let’s answer the most frequently asked questions about what a relational database is:

Is SQL a relational database?

SQL (Structured Query Language) is not a relational database itself; rather, it is a language used to interact with relational databases. Relational databases, like Retable, use a simplified and modified version of a query language model to perform operations such as querying, updating, and managing data stored in relational tables.

What is an example of relational database?

An example of a relational database is Retable. Retable allows users to create relational tables where data is organized into rows and columns, and relationships between different tables can be established using primary and foreign keys. This enables users to efficiently manage and analyze interconnected data sets.

What are the 3 types of relational database model?

The three types of relational database models are:

1. Relational Database schema: This defines the structure of the database, including the tables, fields, and relationships between them.

2. Relational tables: These are the basic building blocks of a relational database, consisting of rows (records) and columns (fields).

3. Relational database theory: This encompasses the principles and concepts underlying relational databases, such as data integrity, normalization, and relational algebra.