Database normalization is a process used to organize a database into tables and columns to minimize redundancy and dependency. The main goal of normalization is not necessarily performance improvement, but rather data integrity and logical correctness.
Normalization helps avoid anomalies that arise when you insert, delete, or update records in your database. It also ensures that each piece of data is only stored in one place, reducing redundancy and inconsistency.
However, the effect of normalization on performance can be complex:
Query Performance: Normalization can lead to increased complexity in queries, because data often has to be gathered from many different tables. Join operations are expensive in terms of computational resources, which can negatively affect performance.
Write Performance: On the other hand, write operations (INSERT, UPDATE, DELETE) might be faster with normalized designs since they deal with less redundant data.
Disk Space Usage: Normalization reduces redundancy and thus, typically uses less disk space. This reduced disk I/O can potentially increase performance.
Here's an example for clarification:
In the non-normalized version, if a student is enrolled in multiple courses, there will be redundant entries for
StudentName. If we need to change the name of a student, we would have to do it in multiple places, which increases the chance of errors. In the normalized version, each piece of information is only stored once, reducing redundancy and chances of errors.
In conclusion, normalization leads to better data integrity and can improve write performance and reduce disk space usage. However, it can also make queries more complex and potentially slow down read operations. Therefore, decisions about normalization should take into account the specific needs and workload characteristics of your database.