Database Enums

So is it better to store enumerated types in a database as a string/varchar or integer?  Well it depends, but in general as a string is your best bet.  In this post I explore the pros and cons of each.

Lists verse Enums

Before we get to that let’s first be clear that I’m talking about enums here, not lists.  Let me explain the difference.

For example let’s say to have a list of a available weight units: pounds, kilograms, grams, short tons, metric tons, long tons, stones, ounces, and etcetera.  You might be able to design your database so that the list of possible weight units is in a table.

Your application should not have any advanced knowledge of the weight units that are defined in this table.  The application reads this dynamic list at run time.  Any information needed about these weight units must come from the database.  This includes conversion factors, display names with multilingual support, flags to indicate in which situations it is appropriate to offer these units as a choice, mapping rules to external systems, and anything else the application may need.  There should be no requirements that pounds must exist as a row or that kilograms must always be ID #1.

If you can soft code every behaviour of the weight unit required by applications in the database then the best design is to soft code this in a table.  Installers may add or remove rows from this table as needed.  This is a “List” of available values, which is defined in a database table.

If the available weight units is hard coded into the application as an enum or strongly typed enum then this is an “enum” not a “list”.  The available values cannot change without changes to the programs.  Therefore the available values should not be a database table.  Adding support for new weight units requires code changes, so it is to the code that you must go to make this change.  Having a database table falsely implies that the values are easy to change.

Lookup Times

The main argument for storing enum values as strings instead of integers is for human readability.  People looking at the database can easily see what the values mean.  Which of these two tables is easier to read?

OrderID Weight WeightUnits
1 14 kg
2 23 lb
3 25 kg
4 11 lb
5 18 kg
OrderID Weight WeightUnitID
1 14 1
2 23 2
3 25 1
4 11 2
5 18 1

Storing the values as a string makes it immediately obvious to anyone looking at the database what the units are.  There is no need have external lookup tables either as database tables, database functions, or external documentation.  It simply makes the system faster and easier to use.

The principle is similar to how applications should be developed so that users can get around with a minimum number of clicks.  Adding just a few hundred milliseconds to the load time of a web page can cost thousands of dollars of lost sales.  Even if the only people looking at the database are your own employees (i.e. a “captive audience”) the lookup time is still burdensome.  Even if users have the IDs memorized, there is still a non-zero amount of time that it takes for the mental jumping jacks to make this conversion.  There is a real cost to this lookup.

Systems should be designed for human readability, not computer readability.


String enum columns usually offer better validation and data quality.  If someone enters a “jf” instead of “kg” for the units it is very obvious that a mistake has been made.  Whereas fat fingers on the number pad entering pressing 2 instead of 1 is much harder to detect.

Having a 1 digit password is not a good idea.  Making your password at least 2 or 3 characters gives much better reassurance that a monkey banging on the keyboard isn’t going to happen upon a valid, yet totally random and incorrect value.

Regardless on whether you choose to have enum values stored as integers or strings, it is a good idea to add a check constraint on the column to limit the values.  In SQL Server, the T-SQL code to add a check constraint is as follows:

Alter Table Orders
Add Constraint CHK_Orders_WeightUnits Check(WeightUnits In ('kg', 'lb'))

There are also pros and cons to adding the check constraint to the database.  The downside is that if you want to enhance your program to support a new enum value you must modify both the program and the database constraint. 

You need to time the upgrades to the application and database.  In general, update the programs to support the new values if the are read from the database, then update the database constraint to allow the new values, then update the applications (or feature toggle) to allow the new values to be written to the database.


I do acknowledge that using integers over strings gives better performance.  Databases are smaller, less data is transferred over the network, and in theory faster.  Exactly how much faster?  I’m not sure, I haven’t run the benchmarks.  Even with storing enums and strings I aim to have all my queries run in a few milliseconds.  In most cases, I would categorize using integers over strings to be a micro-optimization.

However, when creating the enum string values do try to use as little space as possible.  You don’t want to make your enum values dozens of characters long.  Always try to keep these values less than 10 characters.  Try to use abbreviations to reduce the values further down to 2 or 3 characters.  Always use varchar instead of nvarchar.

For normal table columns I don’t think there is a significant performance hit in using strings.  However, one place I might consider using an integer is if the column was used as part of an index.  Database indexes are meant to make databases go fast, therefore every effort should be made to optimize these.

However, it is rare that enum (or Boolean) columns are used in indexes.  In general those types of columns don’t make for good indexes.  The goal of a database index is to take a table with a million rows and narrow that row count down to just the few rows you are searching for.  Dates and free text (e.g. a person’s last name) are good candidates for indexes because they drill down from millions of rows to just a few - quickly.  With an enum with 5 possible values, including the enum in the index is only going to reduce the millions of rows by a fifth (still hundreds of thousands).

If there is an enum value that does significantly reduce the row count, then consider using a filtered index.  Put the enum value in the filter and not directly in the index.  In that case the string enum value isn’t stored in the index; it is just used to decide which rows to put in the index.

Create Index IX_Orders_StatusUnderReview
On dbo.Orders(OrderID)
Where (Status = 'Review')

With this query the “Select * From Orders Where (Status = ‘Review’)” does use this index even though the Status column is not an indexed column.

Print | posted on Wednesday, September 20, 2017 11:38 PM


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