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The pg_trgm extension

Improve Postgres text searches with the pg_trgm extension

The pg_trgm extension enhances Postgres' ability to perform text searches by using trigram matching. Trigrams are groups of three consecutive characters taken from a string. By breaking down text into trigrams, Postgres can perform more efficient and flexible searches, such as similarity and proximity searches.

This extension is particularly useful for applications requiring fuzzy string matching or searching within large bodies of text.

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In this guide, we'll explore the pg_trgm extension, covering how to enable it, use it for text searches, and optimize queries. This extension has applications in data retrieval, text analysis, and anywhere robust text search capabilities are needed.


The pg_trgm extension is open-source and can be installed on any Postgres setup. Detailed information about the extension is available in the PostgreSQL Documentation.

Version availability

Please refer to the list of all extensions available in Neon for up-to-date information.

Currently, Neon uses version 1.6 of the pg_trgm extension for all Postgres versions.

Enable the pg_trgm extension

Activate pg_trgm by running the CREATE EXTENSION statement in your Postgres client:


For information about using the Neon SQL Editor, see Query with Neon's SQL Editor. For information about using the psql client with Neon, see Connect with psql.

Example usage

Let's say you're developing a database of books and you want to find books with similar titles. We first create a test table and insert some sample data, using the query below.

    title TEXT

INSERT INTO books (title)
    ('The Great Gatsby'),
    ('The Grapes of Wrath'),
    ('Great Expectations'),
    ('War and Peace'),
    ('Pride and Prejudice'),
    ('To Kill a Mockingbird'),

Basic string matching

The pg_trgm extension can help you do fuzzy matches on strings.

For example, the query below looks for titles that are similar to the misspelled phrase "Grate Expectation". The % operator, provided by pg_trgm, measures similarity between two strings based on trigrams, and returns results if the similarity is above a certain threshold.

FROM books
WHERE title % 'Grate Expectation';

This query returns the following:

| id | title               |
| 1  | Great Expectations  |

The similarity threshold can be adjusted by setting the pg_trgm.similarity_threshold parameter (default value is 0.3).


Counting trigrams

The pg_trgm module makes these assumptions about how to count trigrams in a text string:

  • Only alphanumeric characters are considered.
  • The string is lowercased before counting trigrams.
  • Each word is assumed to be prefixed with two spaces and suffixed with one space.
  • The set of trigrams output is deduplicated.

We can use the show_trgm function to see how pg_trgm counts trigrams in a string. Here is an example:

SELECT show_trgm('War and Peace'); -- {" a"," p"," w"," an"," pe"," wa",ace,and,"ar ","ce ",eac,"nd ",pea,war}

Computing similarity

Given the set of trigrams for two strings A and B, pg_trgm computes the similarity score as the size of the intersection of the two sets divided by the size of the union of the two sets.

Here is an example.

SELECT show_trgm('War'), show_trgm('Bar'), similarity('War', 'Bar');

This query returns the following:

| show_trgm              | show_trgm              | similarity |
| {" w"," wa","ar ",war} | {" b"," ba","ar ",bar} | 0.14285715 |

There are 7 distinct trigrams across the two input strings and 1 trigram in common. So the similarity score comes out to be 1/7 (0.14285715).

Advanced text searching

pg_trgm offers powerful tools for more complex text search requirements.

Proximity search

The similarity function provided by pg_trgm, returns a number between 0 and 1, representing how similar the two strings are. By filtering on the similarity score, you can search for strings that are within the specified threshold.

SELECT title
FROM books
WHERE SIMILARITY(title, 'War and') > 0.3;

This query returns the following:

| title         |
| War and Peace |

Substring matching

pg_trgm also provides functionality to match the input text value against substrings within the target string. The query below illustrates this:

    word_similarity('apple', 'green apples'),
    strict_word_similarity('apple', 'green apples');

This query returns the following:

| word_similarity | strict_word_similarity |
| 0.8333333       | 0.625                  |

The word_similarity function returns the maximum similarity score between the input string and any substring of the target string. The similarity score is still computed using trigrams. In this example, the first string apple matches with the substring apple in the target.

In contrast, the strict_word_similarity function only considers a subset of substrings from the target, namely only sequences of full words in the target string. That is, the first string apple matches the substring apples in the target, hence the lower score.

Distance scores

There are operators to calculate the distance between two strings, i.e., one minus the similarity score.

SELECT similarity('Hello', 'Halo') AS similarity, 'Hello' <-> 'Halo' AS distance;

This query returns the following:

| similarity | distance  |
| 0.22222222 | 0.7777778 |

Similarly, there are operators to compute the distance based on the word_similarity and strict_word_similarity functions.

Performance considerations

While pg_trgm enhances text search capabilities, computing similarity can get expensive when matching against a large set of strings. Here are a couple of tips to improve performance:

  • Indexing: Using pg_trgm, you can create a GiST or GIN index to speed up similarity search queries. This also helps regular expression-based searches, such as with LIKE and ILIKE operators.

    CREATE INDEX trgm_idx_gist ON books USING GIST (title gist_trgm_ops);
    -- or
    CREATE INDEX trgm_idx_gin ON books USING GIN (title gin_trgm_ops);
  • Limiting results: Use LIMIT to restrict the number of rows returned for more efficient querying.


pg_trgm offers a versatile set of tools for text processing and searching in Postgres. We went over the basics of the extension, including how to enable it and how to use it for fuzzy string matching and proximity searches.


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