In the era of information explosion, more and more data sources are continuously and rapidly producing data. Such data is called streaming data and needs to be analyzed and processed. EventStreamings allow you to process end-to-end streaming data with ease. You can use EventStreamings to extract events from event sources, transform and analyze the events, and then load the events to event targets. The process is known as extract-transform-load (ETL). This topic describes the scenarios, limits, and benefits of EventStreamings. In addition, this topic compares the EventStreaming architecture with the event-driven architecture.

Scenarios

ETL

As more lightweight channels for processing end-to-end streaming data in real time, EventStreamings allow you to filter and transform lightweight streaming data, synchronize data, and connect services to systems. For example, you can use EventStreamings to synchronize data between data warehouses, data processing programs, and data analysis and data processing systems.

The following figure shows that events can flow from event sources to event targets over an EventStreaming without an event bus.

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Message routing or synchronization

EventStreamings can be used to implement various features such as on-cloud message routing, data backup, active geo-redundancy, and data synchronization including cross-account data synchronization and synchronization of data generated by hybrid deployments across data centers. These features help you create an all-in-one solution for processing messages.

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Limits

You cannot create more than 20 EventStreamings in a region.

Benefits

  • Real-time and efficient

    EventStreamings allow you to extract events from event sources and load the events to event targets in real time. In addition, EventStreamings do not allow events to be accumulated. This implements quicker event access and improves the efficiency in responding to business and operational events.

  • Lightweight integration

    EventBridge provides a simple stream model and API operations for you to use EventStreamings. You can manage multiple underlying resources of event-driven data flows with a few steps in the EventBridge console. Alternatively, you can perform the same operations by calling an API operation. This prevents complex operations and facilitates quick integration.

  • Metric monitoring

    EventBridge provides multiple metrics for you to monitor data in EventStreamings. You can set a threshold alert for data flows. This way, you can respond to exceptions at the earliest opportunity to ensure that data flows run as expected.

  • Cost-effective

    No minimum charge is required. You are charged for the amount of data transmitted to EventStreamings. In addition, the EventBridge console provides a data amount dashboard to make fee calculation more transparent. You can configure the data transformation and metric monitoring features as needed. You are not charged if you do not use the features. EventStreamings provide you with more cost-effective event processing solutions compared with the event-driven architecture.

Model comparison

The following figure compares the EventStreaming architecture with the event-driven architecture. The event-driven architecture adopts the N:N structure whereas the EventStreaming architecture adopts the 1:1 structure. The EventStreaming architecture is more lightweight, provides higher dumping efficiency, and does not require you to create event buses.

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