Stream Processing Defined

Stream processing is a Big Data computer programming system, that allows applications to exploit a limited form of parallel processing. It is used to query continuous data streams and detect conditions quickly, within a small time period from the time the data was received. 

Stream processing is also known as real-time analytics, streaming analytics, Complex Event Processing, real-time streaming analytics, and event processing.

Benefits of stream processing include:

• Process massive amounts of streaming events
• Respond in real-time to changing market conditions
• Continuously monitor data and interactions
• Scale according to data volumes
• Remain agile and handle issues as they arise
• Detect interesting relationships and patterns

In Data Defined, we help make the complex world of data more accessible by explaining some of the most complex aspects of the field.

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