What is a Schema in SQL - Advantages, Types

Last updated on July 25th, 2024 at 04:45 am

One of the most common programming languages used to create database management interfaces is Structured Query Language or SQL. Many web-developing companies and web developers have adopted SQL to learn and manipulate data stored in databases. This language is also used to build new tables, indexes and databases as it is the standard programming language for the Relational Database System.

SQL schema is the most essential feature of this language. Keep reading this article to learn more about schema and why it is so important as well as useful!

What is Schema in SQL with Example?

SQL schema definition is one of the most sought-after questions. Schema in SQL are logical data structures that are usually in a dash format and are associated with a database. A schema is always associated with a single database, however, a database can be associated with more than one schema.

A schema is owned by a database user and the username of a database is termed a schema owner. This logical data structure comprises tables, indexes, views, etc. It sets the object of various databases according to the specific objective and relationship.

SQL Schema Example

Schema Name: my_database

Here are the tables:

1. products:

product_id (INT, PRIMARY KEY): Unique ID for each product.

product_name (VARCHAR): Name of the product.

category (VARCHAR): Product category (e.g., "Electronics", "Clothing").

price (DECIMAL): Price of the product.

quantity_in_stock (INT): Current stock level.

2. customers:

• customer_id (INT, PRIMARY KEY): Unique ID for each customer.
• first_name (VARCHAR): Customer's first name.
• last_name (VARCHAR): Customer's last name.
• email (VARCHAR): Customer's email address.

3.  orders:

• order_id (INT, PRIMARY KEY): Unique ID for each order.
• customer_id (INT, FOREIGN KEY): References the customer_id in the customers table.
• order_date (DATE): Date the order was placed.
• total_amount (DECIMAL): Total cost of the order.

4. order_items:

order_item_id (INT, PRIMARY KEY): Unique ID for each item within an order.

order_id (INT, FOREIGN KEY): References the order_id in the orders table.

product_id (INT, FOREIGN KEY): References the product_id in the products table.

quantity (INT): Quantity of the product ordered.

Explanation:

• products: This table stores basic information about the products you sell.
• customers: This table keeps track of your customers.
• orders: This table records individual orders placed by customers.
• order_items: This table details the specific products included in each order, along with the quantities.

Various Components of SQL schema

The schema in DBMS is made up of various components that are extremely essential for efficient work. As a beginner who wants to commence his career as a data scientist, it is essential to know about the various components of SQL schema. Here are a few components of SQL schema that have been explained vividly:

Table

The basic structure of schema in DBMS is laid down by the table feature. The main function of this feature is to maintain all the data inside itself. A table is made up of various rows and columns which are also known as records and fields respectively.

The main task of a table is to give structure to the data that already exists in the database. In a schema table, the original data is stored in the records or rows whereas, the fields presented in the table indicate the data type.  

Index

Index is a schema feature that is closely associated with the table feature. This feature allows a user to retrieve all the deleted data within a few minutes. Hence, with the assistance of the index feature schema improves its performance as well as query execution.

An index can be easily found in a schema table occupying a single column or more than one column.

Columns

One of the most important parts of a database table is columns. It helps a user to understand what type of data has been stored inside the table. Each column has a definite name along with constraints.

Views

Views are just like schema tables but in a virtual format. It can be used as a normal table that can perform data abstraction, access restriction, etc. 

Triggers

The last important component of schema in DBMS is triggers. Its main task is to supervise data integrity along with business logic. Triggers are created so that it can execute itself automatically after certain commands like delete or insert.

A user can enable or disable the triggers feature according to their convenience.

Advantages of Using Schema

SQL schema has many advantages so many companies are rapidly adopting it. Here are a few advantages that have been elucidated properly:

• SQL schema plays a very important role in structuring databases and organising data. It properly structures data by creating indexes as well as tables. This feature of SQL schema allows a web developing company or a web developer to understand and locate the database easily.
• SQL schema provides strong security as well as access control to the existing database in the system. This allows only the authorised members to get access to the internal database and protects it from intruders. The members who have access can easily modify the data and can delete them according to their convenience.
• This feature of SQL is highly scalable and maintainable with databases. It also customises and optimises data according to the current performance.
• Schema allows web developers and administrators to work together as a team on the same database. This results in a higher productivity rate.
• Data schema enhances query performance with the assistance of data management systems, tables, indexes, etc.

How to Create a Schema in SQL?

Certain in-built schema commands are present in the SQL server that can be used to create schema. INFORMATION_SCHEMA, dbo, sys, etc. are some in-built SQL schema examples. To create a schema one must use comment tags that must be enclosed all the object names within double quotes.

Double quotes are also used for special characters which do not consist of numbers, underscore, and letters. If you wish to learn how to create a schema in SQL in more detail, you can enrol in a data analytics course.

Types of Schema in SQL

There are various types of schema in SQL. These various types have been elucidated below:

Star Model

One of the most popular types of data schema is the Star model. Various warehouses have opted for this kind of schema so that they can easily shape the important work-related data. A star model comprises a single fact table that is connected with numerous dimension tables.

All the business-related facts are generally stored in the fact table while all the business data that are present in the fact table is stored in a dimension table.

Snowflake Model

The second type of SQL schema model widely used in warehouses is the snowflake model. It replicates the star model but in a complicated manner. Snowflake models can easily perform advanced analytical works as well as solve complicated doubts about a warehouse.

In a snowflake model structure, there is a single fact table that is interconnected with several dimension tables which are further connected with other required tables. This structure gives a snowflake shape to the SQL schema model. This unique shape allows a warehouse to store more data with little storage space.

Hierarchical Model

The hierarchical schema model is used by various sectors such as the telecommunication sector, banking sector, and healthcare sector. In this model, there is a main root table that is interconnected with several other sub-root tables. The main root table can have several sub-root tables, however, the sub-root tables must originate from a single root table.

The single connection with the sub-root tables reduces the flexibility between databases. This structure of the hierarchical model helps it to quickly perform various actions like deletion, retrieval, etc. 

Galaxy Model

Fact constellation model or galaxy model is one more type of SQL schema. In this model, there are numerous fact tables which are interconnected with numerous dimension tables. This is one of the challenging schema shapes which is very difficult to maintain in the long long-term.

Flat Model

There are many companies that do not require a complicated schema model, for them the Flat model is appropriate due to its simple structure. Simple data castoredstore in this type of schema as there is only one table that contains all the data. The information in a flat model schema is separated with the help of commas.

How to Drop a Schema?

The term dropping a schema in SQL means removing or deleting a schema from a database that has been defined by the user. The “IF EXISTS” command is used to detect and delete an existing schema. Here is a syntax that one can follow to drop schema in DBMS:

Conclusion

SQL schema is one of the most essential topics and a beginner who is willing to commence his or her career in data science and computer application must know the basics. This knowledge will help one to grow in the corporate sector without any hassle.

If you wish to learn more about databases, DBMS and SQL then enrol yourself for the Data Science Course by Imarticus Learning. This 6 months program by expert faculty will help you to learn more about SQL along with practical knowledge. Enrol yourself today to bag lucrative job opportunities!

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