Abstract
In the recent years data processing in Big Data applications are moving from a batch processing model to a live streaming processing model. The live streaming processing model allows to process data in a real time or near real time manner. In many cases, there are need of combining data from various sources - both new generated data and data previously gathered and archived. In each case a different storage mechanism is appropriate to achieve best flexibility and to avoid the so-called bottleneck when processing data. In this article we review some of the possibilities of using Apache Kudu and NoSQL Redis systems which made them suitable to be used together for fast processing of streaming data.
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