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Storing money in a decimal column - what precision and scale? [closed]

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What is precision and scale in decimal?

Precision is the number of digits in a number. Scale is the number of digits to the right of the decimal point in a number. For example, the number 123.45 has a precision of 5 and a scale of 2.

What is precision in money?

For real values, you want to be as precise as the smallest unit of the currency. This means you have no values smaller than a cent, a penny, a yen, a fen, etc.

What data type is money stored as?

Unlike the DECIMAL data type, the MONEY data type is always treated as a fixed-point decimal number. The database server defines the data type MONEY(p) as DECIMAL(p,2). If the precision and scale are not specified, the database server defines a MONEY column as DECIMAL(16,2).

What is the precision of money in SQL Server?

The money data type has a fixed precision: with accuracy to a ten-thousandth of a monetary unit.


If you are looking for a one-size-fits-all, I'd suggest DECIMAL(19, 4) is a popular choice (a quick Google bears this out). I think this originates from the old VBA/Access/Jet Currency data type, being the first fixed point decimal type in the language; Decimal only came in 'version 1.0' style (i.e. not fully implemented) in VB6/VBA6/Jet 4.0.

The rule of thumb for storage of fixed point decimal values is to store at least one more decimal place than you actually require to allow for rounding. One of the reasons for mapping the old Currency type in the front end to DECIMAL(19, 4) type in the back end was that Currency exhibited bankers' rounding by nature, whereas DECIMAL(p, s) rounded by truncation.

An extra decimal place in storage for DECIMAL allows a custom rounding algorithm to be implemented rather than taking the vendor's default (and bankers' rounding is alarming, to say the least, for a designer expecting all values ending in .5 to round away from zero).

Yes, DECIMAL(24, 8) sounds like overkill to me. Most currencies are quoted to four or five decimal places. I know of situations where a decimal scale of 8 (or more) is required but this is where a 'normal' monetary amount (say four decimal places) has been pro rata'd, implying the decimal precision should be reduced accordingly (also consider a floating point type in such circumstances). And no one has that much money nowadays to require a decimal precision of 24 :)

However, rather than a one-size-fits-all approach, some research may be in order. Ask your designer or domain expert about accounting rules which may be applicable: GAAP, EU, etc. I vaguely recall some EU intra-state transfers with explicit rules for rounding to five decimal places, therefore using DECIMAL(p, 6) for storage. Accountants generally seem to favour four decimal places.


PS Avoid SQL Server's MONEY data type because it has serious issues with accuracy when rounding, among other considerations such as portability etc. See Aaron Bertrand's blog.


Microsoft and language designers chose banker's rounding because hardware designers chose it [citation?]. It is enshrined in the Institute of Electrical and Electronics Engineers (IEEE) standards, for example. And hardware designers chose it because mathematicians prefer it. See Wikipedia; to paraphrase: The 1906 edition of Probability and Theory of Errors called this 'the computer's rule' ("computers" meaning humans who perform computations).


We recently implemented a system that needs to handle values in multiple currencies and convert between them, and figured out a few things the hard way.

NEVER USE FLOATING POINT NUMBERS FOR MONEY

Floating point arithmetic introduces inaccuracies that may not be noticed until they've screwed something up. All values should be stored as either integers or fixed-decimal types, and if you choose to use a fixed-decimal type then make sure you understand exactly what that type does under the hood (ie, does it internally use an integer or floating point type).

When you do need to do calculations or conversions:

  1. Convert values to floating point
  2. Calculate new value
  3. Round the number and convert it back to an integer

When converting a floating point number back to an integer in step 3, don't just cast it - use a math function to round it first. This will usually be round, though in special cases it could be floor or ceil. Know the difference and choose carefully.

Store the type of a number alongside the value

This may not be as important for you if you're only handling one currency, but it was important for us in handling multiple currencies. We used the 3-character code for a currency, such as USD, GBP, JPY, EUR, etc.

Depending on the situation, it may also be helpful to store:

  • Whether the number is before or after tax (and what the tax rate was)
  • Whether the number is the result of a conversion (and what it was converted from)

Know the accuracy bounds of the numbers you're dealing with

For real values, you want to be as precise as the smallest unit of the currency. This means you have no values smaller than a cent, a penny, a yen, a fen, etc. Don't store values with higher accuracy than that for no reason.

Internally, you may choose to deal with smaller values, in which case that's a different type of currency value. Make sure your code knows which is which and doesn't get them mixed up. Avoid using floating point values even here.


Adding all those rules together, we decided on the following rules. In running code, currencies are stored using an integer for the smallest unit.

class Currency {
   String code;       //  eg "USD"
   int value;         //  eg 2500
   boolean converted;
}

class Price {
   Currency grossValue;
   Currency netValue;
   Tax taxRate;
}

In the database, the values are stored as a string in the following format:

USD:2500

That stores the value of $25.00. We were able to do that only because the code that deals with currencies doesn't need to be within the database layer itself, so all values can be converted into memory first. Other situations will no doubt lend themselves to other solutions.


And in case I didn't make it clear earlier, don't use float!


When handling money in MySQL, use DECIMAL(13,2) if you know the precision of your money values or use DOUBLE if you just want a quick good-enough approximate value. So if your application needs to handle money values up to a trillion dollars (or euros or pounds), then this should work:

DECIMAL(13, 2)

Or, if you need to comply with GAAP then use:

DECIMAL(13, 4)

4 decimal places would give you the accuracy to store the world's smallest currency sub-units. You can take it down further if you need micropayment (nanopayment?!) accuracy.

I too prefer DECIMAL to DBMS-specific money types, you're safer keeping that kind of logic in the application IMO. Another approach along the same lines is simply to use a [long] integer, with formatting into ¤unit.subunit for human readability (¤ = currency symbol) done at the application level.


The money datatype on SQL Server has four digits after the decimal.

From SQL Server 2000 Books Online:

Monetary data represents positive or negative amounts of money. In Microsoft® SQL Server™ 2000, monetary data is stored using the money and smallmoney data types. Monetary data can be stored to an accuracy of four decimal places. Use the money data type to store values in the range from -922,337,203,685,477.5808 through +922,337,203,685,477.5807 (requires 8 bytes to store a value). Use the smallmoney data type to store values in the range from -214,748.3648 through 214,748.3647 (requires 4 bytes to store a value). If a greater number of decimal places are required, use the decimal data type instead.