About

Event-Data Application are event-driven application that reports / analyze the immutable event collected (without any notion of a pre-defined lifecycle).

An event-driven application is a stateful application that:

• ingest events from one or more event streams delivered by a messaging system
• and reacts to incoming events by triggering computations, state updates, or external actions. They continuously produce and update results as events are consumed.

It's a push model from the perspective of the event creation (because a client may implement a pull model to read the stream of event)

Example

Clickstreams : Suppose you have a website, and every time someone loads a page, you send a user viewed page event to a messaging system. You might then have consumers which do any of the following:

• Store the message in Hadoop for future analysis
• Count page views and update a dashboard
• Trigger an alert if a page view fails
• Send an email notification to another user
• Join the page view event with the user’s profile, and send the message back to the messaging system

Type

• Clickstreams from a website
• Message - Twitter and social media status updates, SMS messages
• Application metrics - monitoring OS or any other application (Network telemetry)
• Log data
• Machine data (IoT) - sensor streams, GPS coordinates
• UI: mouse moves and other UI events

Case

• Fraud detection
• Anomaly detection
• Rule-based alerting
• Business process monitoring
• Web application (social network)
• Real-time search index building
• Continuous ETL
• Large-scale graph analysis

Documentation / Reference

• Traditional ETL vs Continous ETL and OLTP vs Event Driven