Streaming datasets are about doing data processing, not on bounded data, but on unbounded data. Typical datasets are bounded. That means they are complete. At the very least, you will process data as if it were complete. Realistically, we know that there will always be new data, but as far as data processing is concerned, we will treat it as if it were a complete dataset. In the case of bounded data, data processing is done in phases and until and unless one phase is complete, other phases of data processing do not start. Another way to think about bounded data processing is that we will be done analyzing the data before new data comes in. Bounded datasets are finite in size. The following diagram represents how bounded data is processed using a typical MapReduce batch processing engine:
On the other hand, if you have an unbounded dataset (also known as an infinite dataset), it is never complete; there is always new data coming in, and typically, data is coming...