Data Streams and Data Stream Management Systems and Languages

The massive usage of Data Streams dates back to the artificial satellites information processing systems and to their commercial applications exploitation in the early seventies, such as Telecommunications switching, Land Monitoring, Meteorological surveillance, etc.. Today they are extensively used also in monitoring systems applications based on wired and wireless sensor networks, in social networks and in the Internet of Things. The main functional goals of Data Stream Management Systems (DSMSs) are: results must be pushed to the output promptly and eagerly, while input tuples continue to arrive; because of the unbounded and massive nature of the data streams, all past tuples cannot be memorized for future uses. Only synopses can be kept in memory and the rest must be discarded. A key research issue for DSMSs is deciding which data model and query language should be used. A wide spectrum of different solutions have in fact been proposed, including operator-based graphical interfaces, programming language extensions, and an assortment of other solutions provided in publish/subscribe systems. In this chapter, the main features and architectural issues will be examined for DSMSs as an introduction to the following chapters, which detail their usage in different application areas.