Full-text search engines are built for finding and ranking text.

Users rarely search with exact database values. They type partial phrases, misspell words, use synonyms, filter by structured fields, and expect the best results first.

A product search for running shoes size 10 is more than a substring lookup. It needs tokenization, relevance scoring, filters, facets, typo tolerance, and usually business ranking.

Relational databases can provide useful full-text search for many applications.

Dedicated search engines become a better fit when search is a core product feature, the dataset is large, ranking quality matters, or users need features such as autocomplete, highlighting, faceted navigation, and log exploration.

Search engines are usually secondary indexes. The source of truth stays in a database or object store. The search engine stores a searchable copy optimized for retrieval.