Event Stream Processing (ESP) is a technique for real-time analysis of big data. Event Stream Processing, which is used in Event-Driven Architectures
(EDA), continuously analyzes events. As soon as an event occurs, ESP technique can be used to determine the pattern and draw conclusions. The enormous data streams of in Big Data are directly filtered and analyzed. Otherwise, corresponding events would be lost in the data stream and would not be available for analysis, corrections or changes. Due to the timeliness of the analysis, corrections in the configuration or in the algorithms
can be carried out promptly. Thedetected events can be logged or, in terms of errors
caused, handled.Event Stream Processing (ESP) is a technique with which Big Data analytics can be performed in near real-time. ESP technology with real-time analysis and extremely short response times is a key technology for various business models. It can be used in machine control, automobiles, industrial plants in the Internet of Things
(IoT). But it can also be used for event monitoring in financial transactions, detecting Internet fraud or monitoring supply chains. Complex Event Processing (CEP) offers a comparable technology for monitoring, analyzing and controlling complex data streams in real time.