Normalization vs Denormalization
Last updated
What is Normalization vs Denormalization?
Database normalization is a process used to organize a database into tables and columns. The idea is that a table should be about a specific topic and that only those columns which support that topic are included. This limits the number of duplicate data contained within your database. This makes the database more flexible by eliminating issues stemming from database modifications.
Denormalization is the opposite of normalization. It is the process of adding redundant data to a database to improve read performance. This is done by adding duplicate data into multiple tables to avoid expensive joins. This is done at the expense of increased storage and decreased write performance.
Free resources to learn Normalization vs Denormalization
More in stage 17: Databases
Normalization vs Denormalization: common questions
Can I learn Normalization vs Denormalization in Hindi?
This lesson is written in English. Once you sign in, open it in the interactive course and ask the AI tutor to explain Normalization vs Denormalization in Hindi or Hinglish. The tutor answers from this lesson’s own text, so it stays on the syllabus, and it runs on your own Google, OpenAI or Anthropic key.
Is this Normalization vs Denormalization tutorial for beginners?
It is lesson 119 of 188 in the free Computer Science roadmap, in stage 17, Databases. If you are new to Computer Science, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.