Database Schemas: The Beginner's Guide

Athena Ozanich
Athena Ozanich

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The term "database schemas" creates an image of a database filled with shady persons, people known to be — schemas.

Woman studying database schemas on an online educational platform.

Jokes aside, the truth is without database schemas, such a collection of data would be very difficult to accomplish and maintain. The goal of database schemas is to create structure in the way we store our information within a digital platform.

Dumping information into a platform with no method to your madness could easily cause you to fall victim to a wide range of issues.

Database schemas make it possible to collect information in such a way that it maintains its value. By the end of this post, you’ll be able to define a database schema, and understand the difference between schema types and designs.

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What is a database schema?

A database schema is a set of rules that define the architecture of our database and data collection needs. Each company will have its own database needs and will collect different information based on its business goals.

For instance, a store may need to collect transaction information while a free programming education site may only need to collect user information and settings.

Database Schema

Every database schema will make use of all relevant data, consistent formatting, unique identifiers for each object within the schema, and identifiers for any row and column within a table.

Databases are typically managed by a database administrator (DBA), and are responsible for ensuring that the database is accessible to the correct users at the correct user permission levels.

There is more than one kind of database schema, the most common types are the physical database schema and the logical database schema. It is a little bit of a misnomer to think of them as separate types, as they are actually more like two sides of the same coin.

Database Schema Types

The logical and physical database schemas serve different purposes but combined they create a very organized structure for the storage of our data.

Logical Schema vs. Physical Schema

The logical schema defines the structure of the data itself and the relationships between the various attributes, tables, and entries. However, the physical schema defines how the data is stored and managed on the physical hard disk of the devices the database is running on.

Creating a logical database schema is done through the use of visualization tools to illustrate the relationships between entities within the database.
The three most common types of database schemas

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The physical schema is a little different and is largely dependent on the structure of the logical schema. The physical database schema represents how data is stored on the device hard disk. This is the actual code that will be used to create the structure of your database which includes any tables and how they relate to each other.

In MongoDB this is accomplished by creating a mongoose mode, however, with MySQL, you will use SQL to construct a database with tables.

Database Schema Design

Database schema design is dependent on the languages and software you are using as well as the specific database needs of your project. Each database language has a different way of managing the logical data as well as a different method for setting up the physical storage.

NoSQL (Non-relational)

There are however two noteworthy designs that can affect your schemas, the first is non-relational — NoSQL — databases, such as MongoDB. These databases do not use relational schemas to structure data, and many would argue that a schema is not needed for these due to their nature.

However, there are those who would posit that schemas are needed even more due to their non-relational nature. Then you have relational databases like MySQL, SQL, and PostgreSQL, these databases are relational and require a schema to use with any real success.

SQL (Relational)

Relational databases are different and require a schema, in fact, in MySQL the terms database and schema are interchangeable. When defining a relational database in MySQL, you can substitute either term and get the same result.

The relational nature of these databases allows developers to enter a query statement and get back a virtual table — view — of the results of that statement. This virtual table will consist of any entries that are related to the query statement, these entries could be from any number of other tables but are presented as one table.

Database Schema Example

Now that we have a basic understanding of what database schemas are, let's look at a couple of examples of schemas.

NoSQL Database Schema Example

NoSQL databases use a more nested approach for structuring data, information about a car owner would contain within it the information about the car they own.
Example of a NoSQL database schema

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SQL Database Schema Example

SQL databases use multiple tables to organize the various pieces of data, information about a car owner would be kept in a separate table from the information about the car they own.

visual example of a SQL database schema

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Using Database Schemas

Databases seem like they may be confusing at first, but once you understand the difference between the types of databases that exist you can then identify which is best for your needs and comforts.

Each has its own differences but all can meet the needs of your project if you build it correctly. By this point, you should have a better understanding of database schema and be able to make informed decisions about how to approach your project’s database needs.

are data storage and management systems, serving slightly different purposes for your business.

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