Question

I was pointed out by someone else that the following database design have serious issues, can anyone tell me why?

1. a tb_user table saves all the users information
2. tb_user table will have 3 – 8 users only.
3. each user’s data will be saved in a separate table, naming after the user’s name.
   Say a user is called: bill_admin, then he has a seperate table, i.e. bill_admin_data, to save all data belongs to him. All users’ data shared the same structure.

The person who pointed out this problem said I should merge all the data into one table, and uses FK to distinguish them, but I have the following statement:

1. users will only be 3 – 8, so there’s not gonna be a lot of tables anyway.
2. each user has a very large data table, say 500K records.

Is it a bad practise to design database like this? And why? Thank you.

Answer 1

Because it isn’t very maintainable.

1) Adding data to a database should never require modifying the structure. In your model, if you ever need to add another person you will need a new table (or two). You may not think you will ever need to do this, but trust me. You will.

So assume, for example, you want to add functionality to your application to add a new user to the database. With this structure you will have to give your end users rights to create new tables, which creates security problems.

2) It violates the DRY principle. That is, you are creating multiple copies of the same table structure that are identical. This makes maintenance a pain in the butt.

3) Querying across multiple users will be unnecessarily complicated. There is no good reason to split each user into a separate table other than having a vendetta against the person who has to write queries against this DB model.

4) If you are splitting it into multiple tables for performance because each user has a lot of rows, you are reinventing the wheel. The RDBMS you are using undoubtedly has an indexing feature which allows it to efficiently query large tables. Your home-grown hack is not going to outperform the platform’s approach for handling large data.