3.3. FixedPoint Data Types
Fixedpoint data types ensure the predictability of multiplication and division operations, making them the choice for storing monetary values.
Firebird implements two fixedpoint data types: NUMERIC
and DECIMAL
.
According to the standard, both types limit the stored number to the declared scale (the number of digits after the decimal point).
Different treatments limit precision for each type: precision for NUMERIC
columns is exactly as declared
, while DECIMAL
columns accepts numbers whose precision is at least equal to what was declared.
The behaviour of NUMERIC
and DECIMAL
in Firebird is like the SQLstandard DECIMAL
;
the precision is at least equal to what was declared.
For instance, NUMERIC(4, 2)
defines a number consisting altogether of four digits, including two digits after the decimal point;
that is, it can have up to two digits before the point and no more than two digits after the point.
If the number 3.1415 is written to a column with this data type definition, the value of 3.14 will be saved in the NUMERIC(4, 2)
column.
The form of declaration for fixedpoint data, for instance, NUMERIC(p, s)
, is common to both types.
It is important to realise that the s
argument in this template is scale, rather than a count of digits after the decimal point
.
Understanding the mechanism for storing and retrieving fixedpoint data should help to visualise why: for storage, the number is multiplied by 10^{s} (10 to the power of s
), converting it to an integer; when read, the integer is converted back.
The method of storing fixedpoint data in the DBMS depends on several factors: declared precision, database dialect, declaration type.
Precision  Data type  Dialect 1  Dialect 3 

1  4 



1  4 



5  9 



10  18 



3.3.1. NUMERIC
Data Declaration Format
NUMERIC
 NUMERIC(precision)
 NUMERIC(precision, scale)
NUMERIC
Type ParametersParameter  Description 

precision  Precision, between 1 and 18. Defaults to 9. 
scale  Scale, between 0 and scale. Defaults to 0. 
Storage ExamplesFurther to the explanation above, the DBMS will store NUMERIC
data according the declared precision and scale.
Some more examples are:
NUMERIC(4) stored as SMALLINT (exact data)
NUMERIC(4,2) SMALLINT (data * 10^{2})
NUMERIC(10,4) (Dialect 1) DOUBLE PRECISION
(Dialect 3) BIGINT (data * 10^{4})
Always keep in mind that the storage format depends on the precision.
For instance, you define the column type as NUMERIC(2,2)
presuming that its range of values will be 0.99…0.99.
However, the actual range of values for the column will be 327.68..327.67, which is due to storing the NUMERIC(2,2)
data type in the SMALLINT
format.
In storage, the NUMERIC(4,2)
, NUMERIC(3,2)
and NUMERIC(2,2)
data types are the same, in fact.
It means that if you really want to store data in a column with the NUMERIC(2,2)
data type and limit the range to 0.99…0.99, you will have to create a constraint for it.
3.3.2. DECIMAL
Data Declaration Format
DECIMAL
 DECIMAL(precision)
 DECIMAL(precision, scale)
DECIMAL
Type ParametersParameter  Description 

precision  Precision, between 1 and 18. Defaults to 9. 
scale  Scale, between 0 and scale. Defaults to 0. 
Storage ExamplesThe storage format in the database for DECIMAL
is very similar to NUMERIC
, with some differences that are easier to observe with the help of some more examples:
DECIMAL(4) stored as INTEGER (exact data)
DECIMAL(4,2) INTEGER (data * 10^{2})
DECIMAL(10,4) (Dialect 1) DOUBLE PRECISION
(Dialect 3) BIGINT (data * 10^{4})