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A decimal data type could be implemented as either a floating-point number or as a fixed-point number. In the fixed-point case, the denominator would be set to a fixed power of ten. In the floating-point case, a variable exponent would represent the power of ten to which the mantissa of the number is multiplied.
FLOAT (64-bit) DECIMAL, NUMERIC (38 digits) CHAR, VARCHAR, CLOB: BYTE, VARBYTE, BLOB: DATE, TIME, TIMESTAMP (w/wo TIME ZONE) PERIOD, INTERVAL, GEOMETRY, XML, JSON, UDT (User Defined Type) UniData: Dynamic N/A N/A N/A N/A N/A N/A N/A N/A UniVerse: Dynamic N/A N/A N/A N/A N/A N/A N/A N/A Type system Integer Floating point Decimal String Binary ...
A floating-point data type is a compromise between the flexibility of a general rational number data type and the speed of fixed-point arithmetic. It uses some of the bits in the data type to specify an exponent for the denominator, today usually power of two although both ten and sixteen have been used.
The "decimal" data type of the C# and Python programming languages, and the decimal formats of the IEEE 754-2008 standard, are designed to avoid the problems of binary floating-point representations when applied to human-entered exact decimal values, and make the arithmetic always behave as expected when numbers are printed in decimal.
The otherwise binary Wang VS machine supported a 64-bit decimal floating-point format in 1977. [2] The Motorola 68881 supported a format with 17 digits of mantissa and 3 of exponent in 1984, with the floating-point support library for the Motorola 68040 processor providing a compatible 96-bit decimal floating-point storage format in 1990. [2]
The standard type hierarchy of Python 3. In computer science and computer programming, a data type (or simply type) is a collection or grouping of data values, usually specified by a set of possible values, a set of allowed operations on these values, and/or a representation of these values as machine types. [1]
A minifloat is usually described using a tuple of four numbers, (S, E, M, B): S is the length of the sign field. It is usually either 0 or 1. E is the length of the exponent field.
Double-precision floating-point format (sometimes called FP64 or float64) is a floating-point number format, usually occupying 64 bits in computer memory; it represents a wide range of numeric values by using a floating radix point. Double precision may be chosen when the range or precision of single precision would be insufficient.