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What is Full-Text Search? - Definition & Meaning

Learn what full-text search is: searching document content with indexing, stemming, and ranking. Discover Elasticsearch, PostgreSQL, and implementation.

Full-text search is searching within the content of documents or fields, rather than exact string matches. A search index tokenizes text, applies stemming/lemmatization, and supports fuzzy matches, synonyms, and ranking.

What is What is Full-Text Search? - Definition & Meaning?

Full-text search is searching within the content of documents or fields, rather than exact string matches. A search index tokenizes text, applies stemming/lemmatization, and supports fuzzy matches, synonyms, and ranking.

How does What is Full-Text Search? - Definition & Meaning work technically?

Engines like Elasticsearch, Algolia, Meilisearch, and PostgreSQL tsvector index text for fast queries. Features: stemming, fuzzy (typo tolerance), faceted search, highlights. Ranking via TF-IDF or BM25. At MG Software we use full-text search for knowledge bases, product catalogs, and document management.

How does MG Software apply What is Full-Text Search? - Definition & Meaning in practice?

MG Software implements full-text search in client applications: product search, knowledge base search, document retrieval. We choose PostgreSQL FTS for simple cases, Elasticsearch or Meilisearch for advanced search experiences.

What are some examples of What is Full-Text Search? - Definition & Meaning?

  • An e-commerce site where customers search by product name, description, and attributes with typo tolerance and filters.
  • A knowledge base where articles are full-text searchable with snippet highlighting in results.
  • A DMS where documents are searchable by content, including PDF text via OCR.

Related terms

document managementdocumentationapisaas

Further reading

Knowledge BaseWhat is an API? - Definition & MeaningWhat is DevOps? - Definition & MeaningSearch Functionality Examples - Inspiration & Best PracticesElasticsearch vs Algolia: Complete Comparison Guide

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Frequently asked questions

PostgreSQL tsvector suffices for simple search and smaller datasets; no extra infra. Elasticsearch scales better, offers facets, aggregations, and advanced ranking. For >100k documents or complex queries: Elasticsearch.
Relevant ranking (BM25 tuning), synonyms, spell correction, facets for filtering. A/B testing search terms and user behavior analysis help.
Without an index, every query would require a full table/collection scan. An inverted index enables search in milliseconds instead of seconds.

PostgreSQL full-text or Elasticsearch?

PostgreSQL tsvector suffices for simple search and smaller datasets; no extra infra. Elasticsearch scales better, offers facets, aggregations, and advanced ranking. For >100k documents or complex queries: Elasticsearch.

How do you improve search results?

Relevant ranking (BM25 tuning), synonyms, spell correction, facets for filtering. A/B testing search terms and user behavior analysis help.

Why is indexing important for full-text search?

Without an index, every query would require a full table/collection scan. An inverted index enables search in milliseconds instead of seconds.

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