What is the need for Denormaliation?
Denormalization is a database optimization technique in which we add redundant data to one or more tables. This can help us avoid costly joins in a relational database. Note that denormalization does not mean not doing normalization. It is an optimization technique that is applied after doing normalization.
Which are valid reasons to Denormalize a production database?
In order to improve performance is almost always the answer. In the relational database environment, denormalization can mean fewer objects, fewer joins, and faster access paths. These are all very valid reasons for considering it.
When do you need to DENORMALIZE a database?
In many cases, the need for denormalization has waned as computers and RDBMS software have become more powerful, but since data volumes have generally increased along with hardware and software performance, OLAP databases often still use denormalized schemas.
What’s the purpose of denormalization in a website?
The main purpose of denormalization is to significantly speed up data retrieval. However, denormalization isn’t a magic pill. Developers should use this tool only for particular purposes: Learn how to optimize your website speed by improving the backend.
How to avoid a table join in denormalization?
We can avoid a table join by denormalizing the Messages table through adding the first_attachment_name column. Naturally, if a message contains more than one attachment, only the first attachment will be taken from the Messages table while other attachments will be stored in a separate Attachments table and, therefore, will require table joins.
What’s the difference between denormalization and normalization?
As the name suggests, denormalization is the opposite of normalization. When you normalize a database, you organize data to ensure integrity and eliminate redundancies. Database denormalization means you deliberately put the same data in several places, thus increasing redundancy. “Why denormalize a database at all?” you may ask.