The correct choice is Neptune. It is AWS’s managed graph database designed specifically for storing and traversing highly connected data with low-latency multi-hop queries. It supports Gremlin and SPARQL, which are purpose-built graph query languages ideal for friends-of-friends patterns and similar traversals. The option Amazon Redshift is incorrect because it is a columnar data warehouse for analytical SQL workloads, not for native graph traversals. The option Amazon Aurora is incorrect because relational schemas require multiple joins for multi-hop relationships, which is less efficient than a graph engine. The option Amazon Keyspaces is incorrect because it is a wide-column store compatible with Cassandra, lacking native graph traversal semantics. Keywords such as graph, traversal, multi-hop, friends-of-friends, Gremlin, or SPARQL are strong signals for Neptune. Map use cases to purpose-built databases quickly: graph ⇒ Neptune. Analytics warehouse ⇒ Redshift. Relational OLTP ⇒ Aurora. Wide-column ⇒ Keyspaces.