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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