What type of data structure is recommended for non-standard hierarchy scenarios?

In scenarios where non-standard hierarchies need to be represented, a ragged hierarchy is particularly suitable. Unlike traditional hierarchies that have consistent levels, a ragged hierarchy accommodates situations where different branches of the hierarchy may have varying numbers of levels. This flexibility allows for more complex data relationships to be accurately modeled, particularly when dealing with organizational structures or product categories that do not follow a set pattern.

For example, in a corporate structure, one division may have several layers of management, while another may have fewer layers, requiring a data model that can handle these discrepancies in depth. Ragged hierarchies are specifically designed for such use cases where the depth of each branch can vary, making them highly effective in capturing and analyzing data that does not conform to standard levels or structures.

In contrast, level hierarchies are best suited for scenarios where a fixed number of levels exist, parent-child hierarchies are effective for clear parent-child relationships but may not manage varying depths well, and flat hierarchies simply list entities without hierarchical relationships, which removes the complexity often needed in non-standard scenarios. Thus, ragged hierarchies provide the necessary structure to accurately depict and analyze these non-standard relations.