Which service is optimized for storing and querying highly connected datasets?

The service optimized for storing and querying highly connected datasets is Amazon Neptune. This fully managed graph database service is designed specifically for applications that require efficient storage and querying of graph data. It supports popular graph models such as property graphs and RDF (Resource Description Framework), allowing for complex relationships and connections between data points to be modeled efficiently.

Neptune excels in scenarios where the relationships between data points are as important as the data itself, such as social networks, recommendation engines, and fraud detection systems. The ability to perform powerful queries on interconnected data makes it particularly suited for applications requiring deep traversal of relational data, which is a common characteristic in graph databases.

In contrast, Amazon Redshift is a data warehouse service primarily meant for large-scale data analytics but does not optimize for the complex relationships inherent in graph datasets. Similarly, Amazon DynamoDB is a NoSQL database optimized for key-value and document data, and while it handles relationships to some extent through secondary indexes, it does not provide the same level of graph-centric capabilities as Neptune. Amazon DocumentDB, while designed for document-oriented storage, also does not focus on graph relationships but rather on structured data. Thus, Amazon Neptune stands out as the appropriate choice for highly connected datasets.