Event Stream Processing consists of two separate technologies. The first form of technology is a system that logically stores Events, and the second type is software used to process Events.<p>The first component is responsible for data storage and saves information based on a timestamp. As an illustration of Streaming Data, recording the outside temperature every minute for a whole day is an excellent example. In this scenario, each Event consists of the temperature measurement and the precise time of the measurement. Stream Processors or Stream Processing Engines constitute the second component.<p>Most often, developers use Apache Kafka to store and process Events temporarily. It also enables the creation of Event Streams-based pipelines in which processed Events are transferred to further Event Streams for additional processing.