Full text search (FTS) in Couchbase allows developers to query natural language data without requiring additional tooling like Elasticsearch. FTS enables users to perform searches on unstructured data, such as text documents, and provides features like facets, which aggregate information collected on a result set. Facets are useful for categorization of result data, and can be used to narrow down search results. To get started with FTS in Couchbase, developers need to create an index that specifies the fields to search against, including any facet fields. This can be done using the Couchbase administrative dashboard or through the Node.js SDK. Once an index is created, developers can use the `SearchQuery` and `SearchFacet` classes in the Node.js SDK to perform searches with facets. The results of a FTS query include the document key and any facet terms that match the search criteria. Developers can also use conjunctive queries to combine multiple search terms and narrow down their results. By using FTS and the Node.js SDK, developers can build powerful search applications that leverage natural language data in Couchbase databases.