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Editorial Team
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Editorial Team
Asked: May 15, 20262026-05-15T14:32:47+00:00 2026-05-15T14:32:47+00:00

I am just curious how do you all create tables to maintain integrity? tblUserProfile

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I am just curious how do you all create tables to maintain integrity?

tblUserProfile

UserId
EyeColorId
HairColorId
RelationShipStatusId

etc.

Each of these values like EyeColorId has a set of values like Brown,Black,Yellow,Green. Similary HairColorId has black, blonde, crimson etc and RelationShipStatusId has Divorced, Married, Single etc. Should i create different tables for each one of these? like

tblEyeColor

EyeColorId
EyeColorCode

then :-

tblHairColor

HairColorId
HairColorCode

and likewise keep creating tables? There are many such tables(approximately 20-25). If i keep creating these tables and make joins on them, it will terribly slow down my performance. How do you all maintain this sort of enum values? Should i keep a check constraint or should i keep making tables?

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1 Answer

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  1. Editorial Team
    Editorial Team
    2026-05-15T14:32:48+00:00Added an answer on May 15, 2026 at 2:32 pm

    I would say that Color looks like it could be a single table that both hair and eye could both use. How important is it to your integrity to enforce the fact that no one should have blonde eyes or blue hair?

    Some people go with the idea of a single lookup table, which would have an id, a group, and a value and perhaps a description for each row. The id and group would be the primary key, so you’d have id = 1 and group = 1 for hair as the BLONDE hair color, id = 1 and group = 2 for eyes as the HAZEL eye color, etc.

    Others would deride this as a poor denormalized design.

    The joins will only slow you down when the number for a particular query gets large.

    My advice would be to do a normalized design until you have some data to suggest that it’s performing poorly. When that happens, profile your app to find out where the problem is and refactor or denormalize appropriately.

    I would say that indexing will have a greater impact on your performance than these JOINs. You might be guilty of premature optimization without data to support it.

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