Create a Search Engine with SurrealDB Full-Text Search

SurrealDB has integrated a powerful Full-Text Search capability that allows for efficient and accurate searches across large datasets, distinguishing itself from basic pattern-matching functions like string::contains. The Full-Text Search in SurrealDB is built on core concepts such as tokenizers, filters, and analyzers, which process text data to offer a more versatile and scalable searching capacity. This functionality is seamlessly integrated with SurrealDB's query language, SurrealQL, allowing developers to maintain consistency across data operations and search queries. The database offers ACID compliance to ensure data integrity and scales its search capabilities alongside the database. SurrealDB also supports integrated faceted search, enabling developers to create complex search queries with advanced relevance scoring mechanisms, exemplified by a built search engine for Linux-related books. By using custom analyzers and tokenizers, developers can tailor searches to meet specific dataset demands, enhancing the usability and precision of search results.