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How Do I Find Similar Names in SQL?

Published in Database & SQL 2 mins read

Finding similar names in SQL involves comparing strings for likeness. This can be achieved using various techniques, including:

1. Soundex Function

The Soundex function converts a string to a phonetic code, allowing you to identify words that sound alike. This is useful for finding names with similar pronunciation even if they have different spellings.

Example:

SELECT *
FROM customers
WHERE SOUNDEX(firstName) = SOUNDEX('Smith');

This query will return all customers with first names that sound like "Smith," including "Smyth," "Schmidt," and "Smithe."

2. Levenshtein Distance

The Levenshtein distance measures the minimum number of edits (insertions, deletions, or substitutions) required to transform one string into another. This metric can be used to find names that are similar in spelling, even if they have a few differences.

Example:

SELECT *
FROM customers
WHERE levenshtein(firstName, 'John') <= 2;

This query will return all customers with first names that are within two edits of "John," including "Jon," "Johan," and "Joann."

3. Regular Expressions

Regular expressions provide flexible pattern matching capabilities. You can use them to search for names that match specific patterns, like those with similar prefixes, suffixes, or internal characters.

Example:

SELECT *
FROM customers
WHERE firstName LIKE 'J%n';

This query will return all customers with first names starting with "J" and ending with "n," including "John," "Jane," and "Jonathan."

4. Fuzzy Matching

Fuzzy matching algorithms, like Jaro-Winkler or Trigram, are designed to find similar strings even with significant differences. These algorithms analyze the characters and their positions within the strings to determine their similarity.

Example:

SELECT *
FROM customers
WHERE jaro_winkler_similarity(firstName, 'John') > 0.8;

This query will return all customers with first names having a Jaro-Winkler similarity score greater than 0.8 with "John," indicating a high degree of similarity.

5. Custom Similarity Functions

You can create custom functions in SQL to define your own similarity criteria based on specific requirements. This allows you to tailor the search to your specific needs, such as considering only names with similar lengths or specific character combinations.

Example:

CREATE FUNCTION custom_similarity (str1 VARCHAR, str2 VARCHAR)
RETURNS INT
BEGIN
  DECLARE similarity INT;
  -- Define your similarity logic here
  -- For example, compare lengths and common substrings
  SET similarity = ...;
  RETURN similarity;
END;

SELECT *
FROM customers
WHERE custom_similarity(firstName, 'John') > 5;

This example creates a custom function custom_similarity that can be used to find names based on your defined similarity criteria.

Remember to choose the technique that best suits your specific needs and data characteristics. You can combine different methods for more comprehensive results.

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