Virginie Taborowski
Content Specialist
Last updated on
3.3.25
Best Practice
Creating a relational database model: step-by-step guide
9
min
Table of contents
- Definition: What is a relational database model?
- The development of relational databases
- The key concepts of the relational database model
- ACID properties of relational databases
- Is SQL a relational database?
- Example: Customer management using relational databases
- The benefits of relational database models
- Tutorial: How to create a relational database model
- Conclusion: Structured data management made easy
Without knowing it, most companies work with relational databases — in customer management, logistics, even when managing construction projects. The structured organization of data in tables enables efficient administration and quick queries. But how do you create a relational database model?
In this guide, you'll learn step by step how to set up a relational database, define data relationships, and develop the optimal structure for your requirements.
Definition: What is a relational database model?
A relational database model organizes data into tables that are related to each other. Each table contains rows (tuples) and columns (attributes). This structure enables you to efficiently store, manage, and query large amounts of data. The model is based on relational algebra and provides a logical view of data, independent of its physical storage. The use of primary and foreign keys ensures consistent and redundancy-free data storage.
The development of relational databases
The relational database model was developed in the 1970s by Edgar F. Codd. Prior to this development, hierarchical and network databases were widely used, but they were difficult to manage. The introduction of the relational model revolutionized database technology as it allowed a clear separation between logical data structure and physical storage. Today, relational databases are the basis of many business-critical applications in almost all industries.
The key concepts of the relational database model
To build and manage a relational database efficiently, it is necessary to understand a few basic concepts. These ensure a structured organization of data and ensure a high level of data integrity.
Tables: Structured storage of data
Data is stored in tables. Each row represents a data set, each column a specific attribute. This structure ensures clear separation and easy management of data.
Primary Key: Unique Identification
The primary key uniquely identifies each row in a table. This prevents duplicate records and ensures data integrity.
Example: A customer number can serve as a primary key.
foreign key: connection between tables
A foreign key references a primary key from another table. This creates relationships between tables, which enable efficient data management. For example, an order table can be linked to the customer table via the customer number.
Normalization: avoid redundancy
Normalization helps to reduce redundant data and maintain data integrity. For this purpose, all information is divided into tables. The database is restructured in such a way that it is available in the so-called normal form, which makes it easier to organize the data.
ACID properties of relational databases
Relational databases have four ACID properties. They ensure that changes to the data within the database (so-called transactions) are reliably processed in the relational database. ACID stands for:
- Atomicity (atomarity): A transaction is either carried out completely or not at all. This prevents the database from remaining in an inconsistent state if a transaction aborts unexpectedly.
- Consistency: A transaction always moves the database from one consistent state to another. This means that all defined integrity conditions and rules are met even after the transaction.
- Isolation (Isolation): Transactions that take place in parallel do not influence each other. Each transaction is treated as if it were the only operation in progress, preventing data conflicts.
- Durability: After a transaction is completed, the changes made are permanently stored in the database, even in the event of a system failure. Durability is ensured by mechanisms such as log files or redundant storage.
Is SQL a relational database?
SQL (Structured Query Language) is not a relational database, but the standardized language for managing relational databases. SQL allows you to query, insert, update, and delete data. Common relational database systems include MySQL, PostgreSQL, and Microsoft SQL Server.
Example: Customer management using relational databases
A CRM system is often based on relational databases to manage customer information in a structured way. The central customer table contains essential data such as name, address and contact details. Using foreign keys, it is linked to other tables such as orders and products. In this way, the system can retrieve each customer's order history, assign products and enable targeted analyses.
This structure not only allows efficient administration, but also supports automation, for example for personalized offers or automatic invoicing.
The benefits of relational database models
Relational databases offer numerous benefits that make them a preferred choice for companies:
- Structured and organized data storage: The table structure with primary and foreign keys allows data to be stored logically and comprehensibly.
- High data integrity: Compliance with normalization rules reduces redundancies and ensures that data remains consistent.
- Flexibility and scalability: Relational databases grow with a company's requirements and can efficiently manage large amounts of data.
- Efficient queries and reports: With SQL, you can carry out targeted queries and generate reports to make business-relevant information quickly available.
- Multi-user access: Multiple users can access the database at the same time without creating inconsistencies.
- Safety: User rights and roles can be used to specifically protect sensitive data and prevent unauthorized access.
Tutorial: How to create a relational database model
A relational database model provides a structured way to store and manage data. It is based on tables that are interrelated and enable consistent data organization.
The following guide takes you through the essential steps to create such a model:
Step 1: Define requirements and goals
Before you start modeling, you should carefully analyze your database requirements. This includes:
- A detailed description of the data that is to be saved.
- The identification of the most important business processes that must be supported by the database.
- Defining the relationships between different data units.
Create an initial sketch that roughly shows which entities are necessary and how they interact with each other.
Step 2: Identify Entities and Attributes
Entities are the central objects within a relational database system. Each entity represents a specific category of data. In doing so, you should:
- Systematically record all relevant entities (e.g. customer, product, order).
- Determine the associated attributes for each entity (e.g. name, address, price, order date).
- Set the appropriate data type for each attribute (e.g. strings for names, numeric values for prices, date formats for timestamps).
Step 3: Set primary and foreign keys
A well-designed relational model requires primary keys to uniquely identify each record instance. The following applies:
- Each entity should have a unique primary key (e.g. customer number, order number).
- Foreign keys are used to establish relationships between tables. A foreign key references a primary key from another table and ensures that there are no illegal or orphaned entries.
Step 4: Define relationships between tables
The type of relationships between the entities is essential for the structure of the database. The basic relationship types are:
- 1:1 relationship: One entity is assigned exactly to another (e.g. a person has an identity card).
- 1:n relationship: An entity can be linked to several others, but not vice versa (e.g. a customer can place multiple orders, but an order belongs only to one customer).
- m:n relationship: Both entities can be linked to each other multiple times (e.g. a student can attend multiple courses, and a course has multiple students). To correctly implement an m:n relationship, an intermediate table is required.
Step 5: Perform normalization
Normalization ensures that the database works efficiently and avoids redundancies. Key normalization stages include:
- 1st normal form (1NF): All attributes only contain atomic values that cannot be further divided.
- 2nd normal form (2NF): All non-key attributes are functionally dependent on the entire primary key combination.
- 3. Normal form (3NF): There are no transitive dependencies between non-key attributes.
By applying these rules, a flexible, maintainable and scalable database structure is created.
Step 6: Select a relational database management system (RDBMS)
After modeling, you need a platform to implement it. Ninox is a cloud-based, relational database management system that is intuitive to use and quick to implement. Especially for companies that need a powerful database solution without in-depth SQL knowledge, Ninox offers a flexible and customizable environment. Thanks to visual modeling and automation options, you can efficiently implement and manage your relational database model.
Try Ninox free for 30 days now!
Conclusion: Structured data management made easy
A relational database model provides an efficient and structured way to store and manage data. Through clear organization in tables, the use of primary and foreign keys, and compliance with normalization rules, the database remains consistent and powerful. With a suitable RDBMS such as Ninox, the model can be quickly implemented and flexibly adapted — ideal for companies that need a scalable and secure solution.
