Graph databases are typically avoided in interviews unless which query pattern is central to the application?

Graph databases are typically avoided in interviews unless which query pattern is central to the application?

• A. Relationship traversal is the core query pattern
• B. Time-series aggregation
• C. Append-only writes
• D. Full-text search

Answer: (A)

Graph databases shine when the primary workload is traversing relationships between entities. They model data as nodes and edges, allowing efficient path queries where you follow connections across hops. In interviews, they’re typically avoided unless the application’s main query pattern involves discovering or reasoning about relationships, paths, and network structures. If the task is time-series aggregation, specialized time-series databases handle large-scale windowed computations efficiently. If you’re mainly appending events, a log-structured or append-only store fits better. For full-text search across documents, a dedicated search engine provides optimized indexing and ranking. When relationship traversal is central, a graph database makes modeling and querying natural, expressive, and performant, which is why this is the scenario highlighted.

Graph databases shine when the primary workload is traversing relationships between entities. They model data as nodes and edges, allowing efficient path queries where you follow connections across hops. In interviews, they’re typically avoided unless the application’s main query pattern involves discovering or reasoning about relationships, paths, and network structures. If the task is time-series aggregation, specialized time-series databases handle large-scale windowed computations efficiently. If you’re mainly appending events, a log-structured or append-only store fits better. For full-text search across documents, a dedicated search engine provides optimized indexing and ranking. When relationship traversal is central, a graph database makes modeling and querying natural, expressive, and performant, which is why this is the scenario highlighted.