नोट
इस पृष्ठ तक पहुंच के लिए प्राधिकरण की आवश्यकता होती है। आप साइन इन करने या निर्देशिकाएँ बदलने का प्रयास कर सकते हैं।
इस पृष्ठ तक पहुंच के लिए प्राधिकरण की आवश्यकता होती है। आप निर्देशिकाएँ बदलने का प्रयास कर सकते हैं।
Applies to: 
SQL Server 2025 (17.x)
Azure SQL Database
Azure SQL Managed Instance
SQL database in Microsoft Fabric
Note
As a preview feature, the technology presented in this article is subject to Supplemental Terms of Use for Microsoft Azure Previews.
Calculates a similarity value ranging from 0 (indicating no match) to 100 (indicating full match).
Note
EDIT_DISTANCE_SIMILARITYis currently in preview.EDIT_DISTANCE_SIMILARITYcurrently doesn't support transpositions.- SQL Server support for
EDIT_DISTANCE_SIMILARITYintroduced in SQL Server 2025 (17.x). EDIT_DISTANCE_SIMILARITYis available in Azure SQL Managed Instance with the SQL Server 2025 or Always-up-to-date update policy.
Syntax
EDIT_DISTANCE_SIMILARITY (
character_expression
, character_expression
)
Arguments
character_expression
An alphanumeric expression of character data. character_expression can be a constant, variable, or column. The character expression can't be of type varchar(max) or nvarchar(max).
Return types
int
Remarks
This function implements the Damerau-Levenshtein algorithm. If any of the inputs is NULL then the function returns a NULL value. Otherwise, the function returns an integer value from 0 to 100. The similarity value is computed as (1 – (edit_distance / greatest(len(string1), len(string2)))) * 100.
Examples
The following example compares two words and returns the EDIT_DISTANCE_SIMILARITY() value as a column, named Distance.
SELECT 'Colour' AS WordUK,
'Color' AS WordUS,
EDIT_DISTANCE_SIMILARITY('Colour', 'Color') AS Distance;
Returns:
WordUK WordUS Distance
------ ------ -----------
Colour Color 83
For additional examples, see Example EDIT_DISTANCE_SIMILARITY().