Fuzzy Text Search in PostgreSQL: How Trigrams Make Computers "Almost Right"
The article discusses the concept of fuzzy text search in PostgreSQL, focusing on the use of trigrams. Trigrams are groups of three consecutive characters that help computers understand and match similar words despite minor typos. This method improves search accuracy by allowing for a more human-like understanding of text input.
- ▪Fuzzy search teaches computers to find close matches rather than exact ones.
- ▪Trigrams are groups of three consecutive characters from a word, which help in measuring similarity between words.
- ▪PostgreSQL uses trigrams to calculate similarity based on shared trigrams between two words.
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| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/dhananjay_haridas_dc11460/fuzzy-text-search-in-postgresql-how-trigrams-make-computers-almost-right-f60 |
| Publication time | Wed, 03 Jun 2026 08:28:48 +0000 |
| Retrieval time | 2026-06-03T08:41:59.255Z |
| Last seen | 2026-06-03T08:41:59.255Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | tN9rm7oujuXL |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3397109) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Dhananjay Haridas Posted on Jun 3 Fuzzy Text Search in PostgreSQL: How Trigrams Make Computers "Almost Right" A deep dive into one of the most clever tricks in database engineering - explained so simply, your grandmother could follow along. The Problem: Computers Are Too Exact Imagine you're searching for a restaurant called "Maharaja Palace" on an app. You type "Maharja Palce" - two small typos. A traditional search engine looks at your input and says: "No results found." Zero.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
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