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Through Streaming analytics, real-time information can be gathered and analyzed from and on the cloud. The information is captured by devices and sensors that are connected to the Internet, as part of the Internet of Things disruption.
Streaming analytics solutions allow organizations to build real-time solutions using IoT and extract information from them later using Big Data, or to churn them first-hand using real-time processing. The power of streaming analytics is such that it allows for the streaming of millions of events in a second and thus allows enterprises to build mission-critical applications that require the performance to be quick and efficient.
Real-time streaming analytics can, for example, present to you the statistics if your latest online ad campaign is working as expected, or if it needs some tweaking to work better. Such applications want to always stay upgraded for performance benefits.
Here are the top platforms being used all over the world for Streaming analytics solutions:
Flink is an open-source platform that handles distributed stream and batch data processing. At its core is a streaming data engine that provides for data distribution, fault tolerance, and communication, for undertaking distributed computations over the data streams. In the last year, the Apache Flink community …
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