Supported data types

This section provides details on the data types used within KDB.AI tables, including name, range/example, brief description, and usage.

In KDB.AI, tables are fundamental structures for storing and organizing data. Here’s a list of supported data types (pytype) in KDB.AI tables:

Pytype	Range/example	Description	Usage
bool	True/False	Binary value	Logical operations and conditions
str	"Hello"	Sequence of characters (letters, numbers, symbols, spaces)	Textual data
uint8	0 to 255	Unsigned integer with 8 bits	Memory-efficient storage in embedded systems
int16	-32,768 to 32,767	Signed integer with 16 bits.	Larger integer values
int32	-2,147,483,648 to 2,147,483,647	Signed integer with 32 bits	General-purpose integer arithmetic
int64	-9,223,372,036,854,775,808 to 9,223,372,036,854,775,807	Signed integer with 64 bits	Large integer computations
float32	3.14, 1.618	Single-precision floating-point number	Real numbers with limited precision
float64	2.718281828459045	Double-precision floating-point number	Provides higher precision than float32
bytes	0 to 255 (8 bits each)	Sequence of bytes (raw binary data)	Handling binary data, such as images or files
datetime64[ns]	An offset from 1970-01-01T00:00:00	A date and time with nanosecond precision	Timestamps and time-based calculations
timedelta64[ns]	An extension of datetime64 with units such as (D)ay, (M)onth, (Y)ear, (h)ours, (m)inutes, or (s)econds	Duration or time difference	Measuring durations or time intervals