Built-in functions

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Applies to

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For more information about built-in functions and their Snowflake equivalents, also see Common built-in functions.

Aggregate Functions

Aggregate functions compute a single result value from a set of input values. (PostgreSQL Language Reference Aggregate Functionsarrow-up-right).

Conditional expressions

PostgreSQL
Snowflake

COALESCEarrow-up-right ( value [, ...] )

COALESCEarrow-up-right ( expression, expression, ... )

GREATESTarrow-up-right ( value [, ...] )

GREATEST_IGNORE_NULLSarrow-up-right ( <expr1> [, <expr2> ... ] )

LEASTarrow-up-right ( value [, ...] )

LEAST_IGNORE_NULLSarrow-up-right ( <expr1> [, <expr2> ... ])

NULLIFarrow-up-right Notes: PostgreSQL's NULLIF ignores trailing spaces in some string comparisons, unlike Snowflake. Therefore, the transformation adds RTRIM for equivalence.

Data type formatting functions

Data type formatting functions provide an easy way to convert values from one data type to another. For each of these functions, the first argument is always the value to be formatted and the second argument contains the template for the new format. (PostgreSQL Language Reference Data type formatting functionsarrow-up-right).

PostgreSQL
Snowflake

TO_CHARarrow-up-right

Notes: Snowflake's support for this function is partial (see SSC-EWI-PG0005arrow-up-right).

TO_DATEarrow-up-right

Notes: Snowflake's TO_DATE fails on invalid dates like '20010631' (June has 30 days), unlike PostgreSQL's lenient TO_DATE. Use TRY_TO_DATE in Snowflake to handle these cases by returning NULL. (see SSC-EWI-PG0005arrow-up-right, SSC-FDM-0032).

Date and time functions

PostgreSQL
Snowflake

CONVERT_TIMEZONEarrow-up-right ( <source_tz> , <target_tz> , <source_timestamp_ntz> )

CONVERT_TIMEZONEarrow-up-right ( <target_tz> , <source_timestamp> )

Notes: PostgreSQL defaults to UTC; the Snowflake function requires explicit UTC specification. Therefore, it will be added as the target timezone.

DATE_PARTarrow-up-right

Notes: this function is partially supported by Snowflake. (See SSC-EWI-PGOOO5arrow-up-right).

DATE_TRUNCarrow-up-right

Notes: Invalid date part formats are translated to Snowflake-compatible formats.

EXTRACTarrow-up-right Notes: Part-time or Date time supported: DAY, DOW, DOY, EPOCH, HOUR, MINUTE, MONTH, QUARTER, SECOND, WEEK, YEAR.

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PostgreSQL timestamps default to microsecond precision (6 digits); Snowflake defaults to nanosecond precision (9 digits). Adjust precision as needed using ALTER SESSION (e.g., ALTER SESSION SET TIMESTAMP_OUTPUT_FORMAT = 'YYYY-MM-DD HH24:MI:SS.FF2';). Precision loss may occur depending on the data type used. Since some formats are incompatible with Snowflake, adjusting the account parameters DATE_INPUT_FORMAT or TIME_INPUT_FORMATarrow-up-right might maintain functional equivalence between platforms.

JSON Functions

PostgreSQL
Snowflake

JSON_EXTRACT_PATH_TEXTarrow-up-right

Notes:

  1. PostgreSQL treats newline, tab, and carriage return characters literally; Snowflake interprets them.

  2. A JSON literal and dot-separated path are required to access nested objects in the Snowflake function.

  3. Paths with spaces in variables must be quoted.

Math functions

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PostgreSQL and Snowflake results may differ in scale.

String functions

String functions process and manipulate character strings or expressions that evaluate to character strings. (PostgreSQL Language Reference String functionsarrow-up-right).

PostgreSQL
Snowflake

OCTET_LENGTHarrow-up-right

Notes: the results may vary between platforms (See SSC-FDM-PG0013).

REGEXP_REPLACEarrow-up-right

Notes: This function includes a parameters argument that enables the user to interpret the pattern using the Perl Compatible Regular Expression (PCRE) dialect, represented by the p value, this is removed to avoid any issues. (See SSC-EWI-0009, SC-FDM-0032, SSC-FDM- PG0011).

SPLIT_PARTarrow-up-right

Notes: Snowflake and PostgreSQL handle SPLIT_PART differently with case-insensitive collations.

STRPOSarrow-up-right (string, substring )

POSITIONarrow-up-right ( <expr1> IN <expr> )

SUBSTRINGarrow-up-right

Notes: Snowflake partially supports this function. PostgreSQL's SUBSTRING, with a non-positive start_position, calculates start_position + number_characters (returning '' if the result is non-positive). Snowflake's behavior differs.

TRIMarrow-up-right

Notes: PostgreSQL uses keywords (BOTH, LEADING, TRAILING) for trim; Snowflake uses TRIM, LTRIM, RTRIM.

Window functions

PostgreSQL
Snowflake

AVGarrow-up-right

Notes: AVG rounding/formatting can vary by data type between PostgreSQL and Snowflake.

DENSE_RANKarrow-up-right

Notes: ORDER BY is mandatory in Snowflake; missing clauses are replaced with ORDER BY 1.

FIRST_VALUEarrow-up-right

Notes: Snowflake needs ORDER BY; missing clauses get ORDER BY <expr>.

LAST_VALUEarrow-up-right

Notes: Snowflake needs ORDER BY; missing clauses get ORDER BY <expr>.

LEADarrow-up-right

Notes: PostgreSQL allows constant or expression offsets; Snowflake allows only constant offsets.

NTH_VALUEarrow-up-right

Notes: ORDER BY is mandatory in Snowflake; missing clauses are replaced with ORDER BY 1.

NTILEarrow-up-right

Notes: ORDER BY is mandatory in Snowflake; missing clauses are replaced with ORDER BY 1. (See SSC-FDM-PG0013).

PERCENT_RANKarrow-up-right

Notes: ORDER BY is mandatory in Snowflake; missing clauses are replaced with ORDER BY 1.

PERCENTILE_CONTarrow-up-right

Notes: Rounding varies between platforms.

ROW_NUMBERarrow-up-right

Notes: ORDER BY is mandatory in Snowflake; missing clauses are replaced with ORDER BY 1.

  • SSC-EWI-PG0005arrow-up-right: Date or time format is not supported in Snowflake.

  • SSC-FDM-0032: Parameter is not a literal value, transformation could not be fully applied

  • SSC-FDM-PG0013: Function syntactically supported by Snowflake but may have functional differences.

  • SSC-EWI-0009: Regexp_Substr Function only supports POSIX regular expressions.

  • SSC-FDM- PG0011: The use of the COLLATE column constraint has been disabled for this pattern-matching condition.

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