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Difference between Denormalization and Normalization

Last Updated: August 26, 2022 by Chaitanya Singh | Filed Under: DBMS

In this guide, you will learn the difference between Denormalization and Normalization.

What is Denormalization

Denormalization is a process of adding redundant data to tables in order to get faster response time for read operations. However this better performance comes with a cost of storing redundant data that occupies additional storage in the database.

Denormalization is covered in detail with examples here.

What is Normalization

Normalization is a process of breaking the table into multiple tables in such a way so that the redundant data is reduced. This removes data inconsistencies and helps maintaining DBMS ACID properties.

Normalization is covered in detail with examples here.

Denormalization vs Normalization

Denormalization Normalization
It provides faster data access as costly time intensive join operations are not required. Data access (or read) is slower as the join operations are required when accessing data from multiple tables.
SQL queries are easy to write as it involves less tables. SQL queries are complex as they usually involve multiple tables.
Redundant data is present. No redundant data exists.
Data inconsistencies are present as same data is available at more than one tables due to data redundancy. No data inconsistencies as normalization removes data redundancy.
Data write operations are slower due to redundant data. Data write operations are faster.
Requires more storage. Requires less storage.

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  3. Types of DBMS
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About the Author

I have 15 years of experience in the IT industry, working with renowned multinational corporations. Additionally, I have dedicated over a decade to teaching, allowing me to refine my skills in delivering information in a simple and easily understandable manner.

– Chaitanya

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