Which service is designed to support graph-based workloads with highly connected data?

• A. Amazon Neptune
• B. Amazon DynamoDB
• C. Amazon RDS
• D. Amazon Keyspaces (for Apache Cassandra)

Answer: (A)

Graph workloads with highly connected data need a database built specifically for graph structures and efficient traversals. Amazon Neptune is a fully managed graph database designed for this use case. It supports both property graphs (via Gremlin) and RDF (via SPARQL), enabling fast traversal across many interconnected nodes and relationships while providing ACID transactions and operational simplicity. This makes it ideal for scenarios like social networks, knowledge graphs, fraud detection, and recommendation engines, where understanding and querying relationships is central.

DynamoDB, while fast and scalable for key-value and document data, isn’t specialized for graph traversals. RDS offers relational databases that excel with structured schemas and joins but can become cumbersome for deep, multi-hop graph queries. Keyspaces (for Apache Cassandra) is a wide-column store optimized for scalable throughput, not graph-specific querying or traversal performance.