Introduction
Data Streaming is an analytic computing framework with its primary focus on speed. The main idea behind these administrators on the requirement of a continuous stream of often unstructured data to be processed. Therefore, data is continuously kept under transformation in memory before it is featured on a disk. This approach is similar to data management by leveraging Hadoop. The primary difference between leveraging Hadoop and Data streaming is the issue of velocity. In the Hadoop cluster, data processing takes place in consequent batches. Speed factor plays a less dominant role in Hadoop than data streaming.
Principles for Data Streaming
Some fundamental principles that define data streaming applications in a real-time environment are as follows.
1. When it is necessary to determine a retail buying opportunity at the engagement point, either via social media or via permission-based messaging.
2. To collect information about the movement covering a secure site.
3. To be able to react to an event that needs an immediate response, such as a service outage or a change in a patient’s medical condition.
4. To calculate the real-time cost that is the variant of dependent variables such as usage and available resources.
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