Data type mapping

This page maps Alteryx Designer data types to SQL data types used by Prophecy pipelines. Prophecy pipelines run on different execution engines such as Databricks SQL, BigQuery, and Snowflake. Because each engine provides its own SQL type system, the resulting data type may differ depending on the configured environment. Use the tabs below to view mappings for your execution engine.

Databricks SQL
BigQuery
Snowflake

String data

Alteryx has four data types for strings: String, WString, V_String, V_WString.In Prophecy, all strings can be handled with the SQL data type STRING.

Alteryx	Prophecy (Databricks SQL)	Notes
`String` / `V_String`	`STRING`	Databricks `STRING` is UTF-8 variable-length. While Alteryx distinguishes between fixed and variable storage, `STRING` covers both use cases.
`WString` / `V_WString`	`STRING`	Databricks strings are Unicode by default. While Alteryx uses a separate wide-string type, `STRING` is effectively wide-string.

Numeric data

Alteryx has seven numeric types: Byte, Int16, Int32, Int64, Fixed Decimal, Float, Double.

Alteryx	Prophecy (Databricks SQL)	Notes
`Byte`	`TINYINT`	Alteryx `Byte` (0–255) becomes signed `TINYINT` (-128–127). Cast to `SMALLINT` if you need a higher positive range.
`Int16`	`SMALLINT`	Two-byte signed integer.
`Int32`	`INT`	Four-byte signed integer.
`Int64`	`BIGINT`	Eight-byte signed integer.
`Fixed Decimal`	`DECIMAL(p,s)`	Defaults to `DECIMAL` with no parameters. Precision and scale can be specified explicitly.
`Float`	`FLOAT`	32-bit single precision (~7 digits).
`Double`	`DOUBLE`	64-bit double precision (~15–16 digits).

DateTime data

Alteryx has three DateTime data types: Date, Time, DateTime.

Alteryx	Prophecy (Databricks SQL)	Notes
`Date`	`DATE`	Calendar date (`YYYY-MM-DD`) without timezone.
`Time`	`STRING` or derived `TIMESTAMP`	Databricks lacks a standalone `TIME` type.
`DateTime`	`TIMESTAMP`	Represents precise time values with microsecond precision.

Precision and range differences

Databricks supports wider date ranges (year 0001–9999).
Alteryx cannot process dates earlier than 1400.
Casting from strings must match the expected format.

Boolean data

Alteryx type: Bool

Alteryx	Prophecy (Databricks SQL)	Notes
`Bool`	`BOOLEAN`	True/False literal values.

Quick reference

Alteryx	Prophecy (Databricks SQL)
String / V_String	`STRING`
WString / V_WString	`STRING`
Byte	`TINYINT`
Int16	`SMALLINT`
Int32	`INT`
Int64	`BIGINT`
Fixed Decimal	`DECIMAL(p,s)`
Float	`FLOAT`
Double	`DOUBLE`
Date	`DATE`
Time	`STRING` or `TIMESTAMP`
DateTime	`TIMESTAMP`
Bool	`BOOLEAN`

String data

Alteryx has four data types for strings: String, WString, V_String, V_WString.In Prophecy, all strings can be handled with the SQL data type STRING.

Alteryx	Prophecy (BigQuery)	Notes
`String` / `V_String`	`STRING`	BigQuery strings are UTF-8 and variable-length.
`WString` / `V_WString`	`STRING`	Unicode strings are supported by default.

Numeric data

Alteryx has seven numeric types: Byte, Int16, Int32, Int64, Fixed Decimal, Float, Double.

Alteryx	Prophecy (BigQuery)	Notes
`Byte`	`INT64`	BigQuery uses a single integer type for all integer widths.
`Int16`	`INT64`	Smaller integer widths are normalized to `INT64`.
`Int32`	`INT64`
`Int64`	`INT64`	Direct mapping.
`Fixed Decimal`	`NUMERIC` or `BIGNUMERIC`	`NUMERIC` supports up to 38 digits precision; `BIGNUMERIC` supports larger precision.
`Float`	`FLOAT64`	Double-precision floating point value.
`Double`	`FLOAT64`	BigQuery uses `FLOAT64` for floating-point values.

DateTime data

Alteryx has three DateTime data types: Date, Time, DateTime.

Alteryx	Prophecy (BigQuery)	Notes
`Date`	`DATE`	Calendar date (`YYYY-MM-DD`).
`Time`	`TIME`	Native time-of-day type without timezone.
`DateTime`	`DATETIME` or `TIMESTAMP`	`DATETIME` has no timezone; `TIMESTAMP` represents an absolute point in time.

Precision and range differences

BigQuery timestamps support microsecond precision.
TIMESTAMP values represent absolute time in UTC.
DATETIME values represent date and time without timezone context.

Boolean data

Alteryx	Prophecy (BigQuery)	Notes
`Bool`	`BOOL`	Represents true/false values.

Quick reference

Alteryx	Prophecy (BigQuery)
String / V_String	`STRING`
WString / V_WString	`STRING`
Byte	`INT64`
Int16	`INT64`
Int32	`INT64`
Int64	`INT64`
Fixed Decimal	`NUMERIC` / `BIGNUMERIC`
Float	`FLOAT64`
Double	`FLOAT64`
Date	`DATE`
Time	`TIME`
DateTime	`DATETIME` or `TIMESTAMP`
Bool	`BOOL`

Known differences & recommendations

Integer widths: BigQuery consolidates all integer sizes to INT64.
Decimal precision: Use NUMERIC for most use cases; use BIGNUMERIC when higher precision is required.
Date/time handling: BigQuery distinguishes between DATETIME (no timezone) and TIMESTAMP (absolute time).
Unicode strings: BigQuery STRING supports UTF-8 text by default.

String data

Alteryx has four data types for strings: String, WString, V_String, V_WString.In a Snowflake fabric, all strings can be handled with the SQL data type VARCHAR.

Alteryx	Prophecy (Snowflake)	Notes
`String` / `V_String`	`VARCHAR`	Snowflake `VARCHAR` supports UTF-8 variable-length strings.
`WString` / `V_WString`	`VARCHAR`	Unicode strings are supported by default.

Numeric data

Alteryx has seven numeric types: Byte, Int16, Int32, Int64, Fixed Decimal, Float, Double.

Alteryx	Prophecy (Snowflake)	Notes
`Byte`	`NUMBER`	Confirm whether Import generates width-specific numeric types or generic `NUMBER`.
`Int16`	`NUMBER`	Snowflake commonly uses `NUMBER` for integer storage.
`Int32`	`NUMBER`
`Int64`	`NUMBER`
`Fixed Decimal`	`NUMBER(p,s)`	Snowflake supports configurable precision and scale.
`Float`	`FLOAT`	Floating-point numeric type.
`Double`	`FLOAT`	Snowflake uses `FLOAT` for double-precision values.

DateTime data

Alteryx has three DateTime data types: Date, Time, DateTime.

Alteryx	Prophecy (Snowflake)	Notes
`Date`	`DATE`	Calendar date without timezone.
`Time`	`TIME`	Snowflake supports a standalone `TIME` type.
`DateTime`	`TIMESTAMP`	Confirm whether Import generates `TIMESTAMP`, `TIMESTAMP_NTZ`, or another timestamp variant.

Precision and range differences

Snowflake supports nanosecond timestamp precision.
Snowflake provides multiple timestamp variants (TIMESTAMP_NTZ, TIMESTAMP_LTZ, TIMESTAMP_TZ).
Timezone behavior depends on the timestamp type and session configuration.

Boolean data

Alteryx type: Bool

Alteryx	Prophecy (Snowflake)	Notes
`Bool`	`BOOLEAN`	Represents true/false values.

Quick reference

Alteryx	Prophecy (Snowflake)
String / V_String	`VARCHAR`
WString / V_WString	`VARCHAR`
Byte	`NUMBER`
Int16	`NUMBER`
Int32	`NUMBER`
Int64	`NUMBER`
Fixed Decimal	`NUMBER(p,s)`
Float	`FLOAT`
Double	`FLOAT`
Date	`DATE`
Time	`TIME`
DateTime	`TIMESTAMP`
Bool	`BOOLEAN`

Known differences & recommendations

Numeric handling: Snowflake commonly uses NUMBER for integer storage.
Timestamp variants: Snowflake supports multiple timestamp types with different timezone semantics.
Unicode strings: VARCHAR supports UTF-8 text by default.
Time support: Unlike Databricks SQL, Snowflake supports a standalone TIME type.

Overview

Alteryx

Informatica

Ab Initio

DataStage

String data

Numeric data

DateTime data

Precision and range differences

Boolean data

Quick reference

String data

Numeric data

DateTime data

Precision and range differences

Boolean data

Quick reference

Known differences & recommendations

String data

Numeric data

DateTime data

Precision and range differences

Boolean data

Quick reference

Known differences & recommendations

​String data

​Numeric data

​DateTime data

​Precision and range differences

​Boolean data

​Quick reference

​String data

​Numeric data

​DateTime data

​Precision and range differences

​Boolean data

​Quick reference

​Known differences & recommendations

​String data

​Numeric data

​DateTime data

​Precision and range differences

​Boolean data

​Quick reference

​Known differences & recommendations

String data

Numeric data

DateTime data

Precision and range differences

Boolean data

Quick reference

String data

Numeric data

DateTime data

Precision and range differences

Boolean data

Quick reference

Known differences & recommendations

String data

Numeric data

DateTime data

Precision and range differences

Boolean data

Quick reference

Known differences & recommendations