This blog post explores the implementation of a FHIR Search REST API Server using Couchbase services, focusing on transforming FHIR search patterns into Couchbase N1QL queries. It provides guidance for organizations developing FHIR-compliant Electronic Health Record systems and highlights the advantages of Couchbase's NoSQL database, including distributed high availability and multi-dimensional scalability. The post discusses setting up a FHIR server using Couchbase and Synthea's synthetic FHIR data, along with detailed examples of various search functionalities such as searching by ID, name, medical identifier, phone, email, and date range. It emphasizes the benefits of using Couchbase N1QL for FHIR data querying due to its support for hierarchical and relational data structures, and the integration of Full Text Search capabilities without the need for external platforms like ElasticSearch or Solr. The blog also addresses the simplicity and efficiency of using Couchbase N1QL's array constructs and ANSI JOINs for processing complex FHIR data models.