Understanding database schema design - a quick guide with examples
August 4, 2023
Picture this: You're a developer working on a new project, and everything seems perfect until you realize your data is scattered all over the place and your code can’t access it efficiently! It feels like a never-ending treasure hunt, and you're racing against time to find the right information. But wait, could this very time-comsuming and chaotic situation have been avoided? By planning and organizing, could all of that scattered information have been consolidated?
In this post, we’ll explore the benefits of a well-thought-out / well-designed database schema by answering the following questions:
A database schema is like a neat and tidy blueprint that gives structure and order to your data. It’s a framework that provides guidance on how data relates to each other and how you can access it. So when applications come knocking, they can easily fetch, play around, and present the information quickly and efficiently.
Think of a database schema as a filing system, like a huge cabinet with lots of drawers, each containing different categories of files. In this analogy, the cabinet is the whole database, and each drawer is a table within the database. Each file in the drawer is a row in the table, and the labels on the files are the columns.
If your filing system is a mess and labeled incorrectly (i.e. your schema is poorly designed) it can be a headache to find what you need and get the data you want from your database. To avoid this, it's important to create a well-organized schema that can easily store and retrieve data.
Tables are the building blocks of a database schema - they contain specific types of data. For example, in a blog database, you can have separate tables for blog posts, authors, and comments. The columns in the tables define the different attributes and characteristics of the data, such as the title, date, and content of a blog post. Connecting the data in these tables is what makes the blog site functional and user-friendly. It allows users to search, navigate, and interact with the content effectively.
This is because database schemas are really all about correlation and association. One of the most powerful features of a schema is the ability to establish relationships between tables. These relationships allow different pieces of information to be connected, creating a cohesive structure. For example, the blog post table can have a column linking it to a corresponding author, so that each blog post is attributed to a writer.
Let's dive a bit deeper into the world of tables and explore how parent-child relationships play an important role in organizing and efficiently connecting data within databases. A parent and child table are two related tables connected through a foreign key relationship. The parent table contains primary data, and the child table holds information related to the data in the parent table.
For instance, in a blog database, we can have
Posts as the parent table and
Comments as the child table. Using SQL, it might look something like the following:
Poststable contains information about the blog posts, such as the post title, content, publication date, and the author of the post.
CREATE TABLE posts ( post_id SERIAL PRIMARY KEY, title VARCHAR(200) NOT NULL, content TEXT, publication_date DATE, author_id INT REFERENCES authors(author_id) );
Commentstable is a child table related to the
Poststable through the
post_idcolumn. It stores comments made by users on specific blog posts, along with the name of the commenter and the comment content.
CREATE TABLE comments ( comment_id SERIAL PRIMARY KEY, post_id INT REFERENCES posts(post_id), commenter_name VARCHAR(100) NOT NULL, comment_content TEXT );
Posts table is the parent table and holds the primary data about the blog posts. The
Comments table is the child table because it is related to the
Posts table through the
post_id foreign key. Each record in the
Comments table is associated with a specific blog post in the
Posts table through a relationship.
This parent-child relationship allows multiple comments to be linked to a single blog post. It helps organize and connect the data in the blog database, so users can view and interact with comments related to each post.
The parent table/ child table is a pretty straight-forward relationship, but database schemas employ other types of relationships. In addition to the parent-child relationship, there are the following:
Usertable and a
Profiletable. Each user has a unique profile, and each profile is associated with only one user.
Posttable can be related to a
Commenttable, like we mentioned earlier. Each post can have multiple comments, but each comment belongs to only one post.
Posttable and a
Tagtable through a junction table called
PostTags. Each post can have multiple tags, and each tag can be associated with multiple posts.
Commenttable, where a comment can be a reply to another comment. Each comment can reference the ID of its parent comment in a
We’ve established that the relationships between tables determine how data is organized, accessed, and maintained within the schema. Relationships play a key role in defining the structure and behavior, but this also depends on the database modelling and the type of database model schema your using.
Data modeling progresses from a high-level conceptual understanding of the data to a structured logical representation, and finally, to the specific implementation in a chosen database model schema, tailored to meet the project's needs
The database model schema acts as a visual representation of the database design.
There are several types of database models and database schemas, each with its own way of organizing and structuring data. The following table outlines the different types:
|Flat model schema||Data is stored in a single table with rows and columns, similar to a spreadsheet.||Schema is simple and easy to implement but may not be suitable for complex data relationships|
|Hierarchical model schema||Organizes data in a tree-like structure with parent-child relationships. Each parent can have multiple children, but each child can have only one parent.||Schema is useful for representing nested data, such as organizational charts.|
|Network model schema||For more complex relationships. Uses a graph-like structure where data items (nodes) are connected to one another through relationships (edges)||Suitable for representing many-to-many relationships.|
|Relational model schema||Based on the concept of tables, rows, and columns. Data is organized in multiple tables, and relationships between tables are established using primary and foreign keys||Widely used and allows for flexible data retrieval using SQL.|
|Entity-relationship model (ER model) schema||Represents entities, attributes, and relationships between entities.||Used to create a conceptual representation of a database before implementing it using a specific schema type.|
|Star schema / Snowflake schema||Organizes data into a central fact table and several dimension tables. The Snowflake schema is an extension of the star schema.||Used in data warehousing and for dimension tables that are normalized to reduce data redundancy.|
|Document model schema||Stores data as semi-structured documents. Data storage is flexible and dynamic.||Used in NoSQL databases.|
|Key-value model schema||Stores data as key-value pairs.||Used in NoSQL databases|
Designing a database schema is undeniably one of the most critical tasks you’ll undertake in your project! It helps keep things organized, prevents duplication, and makes data retrieval easy. A well-designed schema keeps data consistent and accurate and reduces errors. Plus, it speeds up data access for applications. A good database schema design can make or break your project.
Here are 10 pointers (in no particular order) to consider when designing a database schema:
Now that we have an idea of what goes into designing a database schema, let’s apply it to an example. We’ll mix it up and move away from the blog example; let’s see how this can apply to a movie database - something like what we built in our XMDB tutorial (you can also check out this blog post if you want to learn more about how we built XMDB).
Consider a movie database with entities such as
Directors, and their respective attributes:
Moviesentity: Attributes like
Actorsentity: Attributes like
Directorsentity: Attributes like
CREATE TABLE movies ( movie_id SERIAL PRIMARY KEY, title VARCHAR(200) NOT NULL, release_year INT, genre VARCHAR(100), rating NUMERIC(3, 1) ); CREATE TABLE actors ( actor_id SERIAL PRIMARY KEY, full_name VARCHAR(100) NOT NULL, birth_date DATE, nationality VARCHAR(50) ); CREATE TABLE directors ( director_id SERIAL PRIMARY KEY, full_name VARCHAR(100) NOT NULL, birth_date DATE, nationality VARCHAR(50) );
Normalize data: Avoid redundancy. For example, if an actor stars in multiple movies, store the actor details only once in a
actors table and use the
movie_actor table to represent their associations.
Establish relationships: Create relationships between
Directors to represent their associations.
CREATE TABLE movie_actor ( movie_id INT REFERENCES movies(movie_id), actor_id INT REFERENCES actors(actor_id), PRIMARY KEY (movie_id, actor_id) );
ALTER TABLE movies ADD COLUMN director_id INT REFERENCES directors(director_id);
Create indexes on frequently searched columns to optimize query performance. For instance, create an index on the
title column in the
movies table for faster movie title searches.
CREATE INDEX idx_movie_title ON movies(title);
NOT NULLconstraint on the
titlecolumn in the
moviestable, so that a value has to be applied.
ALTER TABLE movies ADD CONSTRAINT chk_movie_title_not_null CHECK (title IS NOT NULL);
Mastering the art of schema design is no easy task, but it’s definitely worth it. Remember these best practices to guide you along the way:
Do you have any valuable tips or suggestions for designing effective database schemas? If there's anything we missed or if you want some extra guidance, don't hesitate to reach out to us; we’d love to hear what you think. If you have any feedback you can join us on Discord or follow us on Twitter.
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