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Home/ Questions/Q 6792559
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Editorial Team
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Editorial Team
Asked: May 26, 20262026-05-26T17:59:06+00:00 2026-05-26T17:59:06+00:00

I think I understand primary keys and indexes. In my setup, I have a

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I think I understand primary keys and indexes.

In my setup, I have a table with several columns. Two of these columns are User ID, and Username.
Ideally I would like both to be unique, and non nullable.

As far as I can tell, my best use would be to have the User ID as the primary key, as this is the most important field not to NULL, and it will never change as the database grows.

I would then have to have the username column as a unique index, so that it can be the same on another row, although unfortunately, could end up NULL.

This is what I will do unless there is a way to have both columns as unique and non NULLABLE?

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  1. Editorial Team
    Editorial Team
    2026-05-26T17:59:06+00:00Added an answer on May 26, 2026 at 5:59 pm

    From both my application development and datawarehouse experience I would recommend having a separate primary key that is not used in any business setting and do not use User ID as the primary key. Using UserID as the primary key can lead to a whole host of problems. I would index each column (separately).

    Anytime you need to merge or reassign a user or change their ID, etc, having actually used their userID as the primary key will lead to a lot of problems for those operations.

    Also, on the web, this will open up people seeing URL’s like ....user/1/details and then potentially being able to change the ‘1’ to a ‘2’ (for example) and seeing other peoples info. It is better if the ID is unique like ‘57489574389ghfjghfjghf’ and then it’s harder to hack URLs with.

    The choice between a ‘natural’ and a ‘surrogate’ key is explained well here:
    http://www.agiledata.org/essays/keys.html

    Most of the problems people experience in this area are for edge cases such as merges and deletes. These are usually of low priority initially but concern over them will grow over time and poorly engineered solutions will start to break down (usually because at the point that data quality is ‘recognized’ there is often such a large volume of ‘bad’ data that going forward is untenable – the old data can’t be ‘fixed’ and without that rules are hard to introduce for new records which will co-exist with them. This assumes that the ability to update old records is still required.

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