The database industry has realized that full-text search and SQL are two sides of the same coin, with text search needing further query processing and query processing requiring efficient filtering for text patterns. As a result, various databases have added full-text search capabilities within themselves. Couchbase Full-Text Search (FTS) is designed to transparently search across multiple fields within a document, providing language-based stemming, fuzzy matching, and relevance-based search results. FTS achieves this on an inverted index and supports aggregation via search facets. In the NoSQL world, Lucene is a popular search index, and Elasticsearch and Solr are search servers based on Lucene that have added SQL support. Couchbase introduced FTS, which has been followed by support for search within N1QL in Couchbase Query service. This allows developers to use SQL-like syntax with full-text search capabilities, providing benefits such as predicates, operators, and functions that enhance query processing and filtering. The integration of FTS with N1QL enables features like join processing, common table expressions (CTEs), and the use of `SEARCH()` in DML statements, making it a powerful tool for querying and manipulating JSON data.