As the data management field has diversified to consider settings in which queries are
increasingly complex, statistics are less available, or data is stored remotely, there has been …

Abstract Many Big Data technologies were built to enable the processing of human
generated data, setting aside the enormous amount of data generated from Machine-to …

Abstract Internet of Things (IoT) is characterized by heterogeneous technologies, which
concur to the provisioning of innovative services in various application domains. In this …

The first edition of this book appeared in 1991 when the technology was new and there were
not too many products. In the Preface to the first edition, we had quoted Michael Stonebraker …

Composite (or Complex) event processing (CEP) systems search sequences of incoming
events for occurrences of user-specified event patterns. Recently, they have gained more …

Scale-out stream processing engines (SPEs) are powering large big data applications on
high velocity data streams. Industrial setups require SPEs to sustain outages, varying data …

Elastic scaling allows a data stream processing system to react to a dynamically changing
query or event workload by automatically scaling in or out. Thereby, both unpredictable load …

The concept of state and its applications vary widely across big data processing systems.
This is evident in both the research literature and existing systems, such as Apache Flink …

A database statement, such as a SQL text, reuses the execution plan compiled for a similar
SQL text found in memory if the value of a system parameter is configured for cursor sharing …

In recent years the processing of continuous queries over potentially infinite data streams
has attracted a lot of research attention. We observed that the majority of work addresses …