Complex event processing: Difference between revisions

Revision as of 12:35, 13 November 2017

Revision as of 16:28, 22 December 2017

Line 30:

==History==

The CEP area has roots in [[discrete event simulation]], the [[active database]] area and some programming languages. The activity in the industry was preceded by a wave of research projects in the 1990s. According to <ref>{{citation|last=Leavit|first=Neal|title=Complex-Event Processing Poised for Growth|url= http://www.computer.org/csdl/mags/co/2009/04/mco2009040017-abs.html|publisher=Computer, vol. 42, no. 4, pp. 17-20 Washington|date=April 2009}}</ref> the first project that paved the way to a generic CEP language and execution model was the Rapide project in [[Stanford University]], directed by [[David Luckham]]. In parallel there have been two other research projects: Infospheres in [[California Institute of Technology]], directed by [[K. Mani Chandy]], and Apama in [[University of Cambridge]] directed by John Bates. The commercial products were dependents of the concepts developed in these and some later research projects. Community efforts started in a series of event processing symposiums organized by the [[Event Processing Technical Society]], and later by the ACM DEBS conference series. One of the community efforts was to produce the event processing manifesto .<ref>[http://drops.dagstuhl.de/opus/volltexte/2011/2985/ Mani K. Chandy and Opher Etzion and Rainer von Ammon(eds), 10201 Executive Summary and Manifesto -- Event Processing, Dagstuhl seminar Procesdings 10201, ISSN 1862-4405, 2011]</ref>

==Related concepts==

Line 101:

* [[GigaSpaces]] XAP

* ''Informatica RulePoint'' by [[Informatica]]

* [[Microsoft|Microsoft StreamInsight]] Microsoft CEP Engine implementation <ref>[https://technet.microsoft.com/en-us/library/ee362541(v=sql.111).aspx Microsoft StreamInsight product page]</ref>

* [[openPDC]] — A set of applications for processing streaming time-series data in real-time.

* [[Oracle SOA Suite|Oracle Event Processing]] - for building applications to filter, correlate, and process events in real time.

* BRMS - A rules management engine by [[Red Hat]] based on [[Drools]]

* [[SAP SE|SAP ESP]] - A low-latency, rapid development and deployment platform that allows processing multiple streams of data in real time <ref>[http://scn.sap.com/community/developer-center/esp SAP ESP - Developers community]</ref>

* [[SAS ESP]] - A platform that is built for speed to analyse (apply SAS' and third-party analytics, including machine learning algorithms) millions of data records in motion (events) with low-latency response time (milliseconds and sub-milliseconds). Deployable at the edge, on premises and to the Cloud. Flexible platform that is built with openness in mind to make Analytics pervasive everywhere. <ref>[https://www.sas.com/en_gb/software/data-management/event-stream-processing.html]</ref>

* [[Sqlstream|SQLstream]] SQLstream’s stream processing platform, s-Server, provides a relational stream computing platform for analyzing large volumes of service, sensor and machine and log file data in real-time.

* [[TIBCO| TIBCO BusinessEvents & Streambase ]] - CEP platform and High Performance Low Latency Event Stream Processing

* [VIATRA-CEP<ref>https://wiki.eclipse.org/VIATRA/CEP VIATRA-CEP]</ref> - A model-driven CEP engine, part of the 3rd generation of the [[VIATRA]] [[model transformation]] framework

* [[WebSphere Business Events]]

* [[WSO2|WSO2 Siddhi]] Complex event processing written in Java. Designed as part of a series of middleware components.

* [[Apache Flink]] Open-source distributed stream processing framework with a [CEP API<ref>https://ci.apache.org/projects/flink/flink-docs-release-1.2/dev/libs/cep.html CEP API]</ref> for Java and Scala.

==References==