Most data is produced continuously. For example, mobile apps, logs, IoT sensors, and so on generate data at a furious pace. Recent data is considered highly valuable, if you act on it in time. These insights can diminish in value or perish with the passage of time. A different set of tools for collecting and analyzing real-time data is required for implementing such applications. The fast pace and variable rates (bursts) of incoming data need to be stored durably and processed correctly, in a continuous, fast, and reliable manner. Typical use cases for such processing include time series analytics, feeding real-time metrics, and generating real-time alarms and notifications. ...
Analyzing streaming data in real time with Amazon Kinesis Analytics
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