Neptune’s interactive performance at scale effectively enables a broad set of graph use cases.

Social networking

Amazon Neptune can quickly and easily process large sets of user-profiles and interactions to build social networking applications. Neptune enables highly interactive graph queries with high throughput to bring social features into your applications. For example, if you are building a social feed into your application, you can use Neptune to provide results that prioritize showing your users the latest updates from their family, from friends whose updates they ‘Like,’ and from friends who live close to them.

1. Metrics: Aggregating statistics from distributed applications to produce centralized feeds of

operational data.

1. Log Aggregation Solution: Kafka can be used across an organization to collect logs from

multiple services and make them available in a standard format to multiple consumers.

1. Stream Processing: Popular frameworks such as Storm and Spark Streaming read data from a

topic, processes it, and write processed data to a new topic where it becomes available for

users and applications.