Hierarchical data structures are prevalent in business applications, capturing parent-child relationships within organizational data such as company structures, sales territories, and financial accounts. Querying these structures efficiently poses challenges for traditional relational database management systems (RDBMS) due to performance issues associated with recursive queries. Established RDBMS like Oracle and SQL Server use constructs such as CONNECT BY to traverse hierarchical data, but this can be inefficient for large data volumes, leading enterprises to flatten hierarchies for better performance. Couchbase's N1QL, a query language for JSON data, offers an alternative by employing a flattened hierarchy approach, which enhances query performance and leverages Couchbase's Global Secondary Indexes (GSI). The N1QL queries use features like ANSI JOIN Support to execute complex hierarchical queries more predictably, although they lack the CONNECT BY keyword, which is specific to Oracle databases. This approach improves data retrieval processes, especially in contexts where hierarchical relationships are complex and dynamic, such as in sales organizations.