Difference between Normalization and Denormalization

Differences Data Structure Database Big Data Analytics

The process to alter the structure of a database is basically categorized into two ways, one is Normalization and the other is Denormalization. The basic difference between normalization and denormalization is that the database normalization removes the redundancy of data and anomalies in a poorly designed table, while denormalization combines multiple table data into one so that it can be queried quickly.

Read through this article to find out more about normalization and denormalization and how they are different from each other.

What is Normalization?

Normalization is used to remove redundant data from the database and to store non-redundant and consistent data into it. It is a process of converting an unnormalized table into a normalized table. Database normalization is an important process because a poorly designed database table is inconsistent and may create issues while performing operations like insertion, deletion, updating, etc.

The process of Normalization involves resolution of database anomalies, elimination of data redundancy, data dependency, isolation of data, and data consistency. Normalization in databases provides a formal framework to analyze the relations based on the key attributes and their functional dependencies. It reduces the requirements of restructuring of tables.

What is Denormalization?

Denormalization is used to combine multiple table data into one so that it can be queried quickly. It is a process of storing the join of higher normal form relations in the form of base relation that is in a lower normal form. The primary goal of denormalization is to achieve the faster execution of the queries.

In the process of denormalization, the data is integrated into the same database. Denormalization is mainly used where joins are expensive and queries are executed on the table very frequently. However, there is a drawback of denormalization, that is, a small wastage of memory.

Difference between Normalization and Denormalization

The following table highlights the important differences between Normalization and Denormalization −

Factor	Normalization	Denormalization
Implementation	Normalization is used to remove redundant data from the database and to store non-redundant and consistent data into it.	Denormalization is the process of adding some redundant data to a database that has been normalized, so as to improve the read performance (execution time) of the database
Focus	Normalization mainly focuses on clearing the database from unused data and to reduce the data redundancy and inconsistency.	The real goal of denormalization is to achieve the faster execution of the queries by introducing redundancy.
Number of Tables	During Normalization, data is reduced, so there will be a decrease in the number of tables.	During Denormalization, data is integrated into the same database and hence there will be an increase in the number of tables.
Memory consumption	Normalization uses optimized memory and hence faster in performance.	Denormalization introduces some sort of wastage of memory.
Data integrity	Normalization maintains data integrity, i.e., any addition or deletion of data from the table will not create any mismatch in the relationship of the tables.	Denormalization does not maintain any data integrity.
Where to use	Normalization is generally used where a number of insert/update/delete operations are performed and joins of those tables are not expensive.	Denormalization is used where joins are expensive and frequent queries are executed on the tables.

Conclusion

Normalization is an important step in designing efficient and functional databases. Normalizing a database involves removing redundancy which means there will be no duplicate entries of the same data. Denormalization is a process that adds some redundant data into a normalized database to enhance its functionality and minimize the running time of specific database queries. You should not confuse a Denormalized database with a database that has not been normalized.