Survey of real-time processing systems for big data

Xiufeng Liu, Nadeem Iftikhar, Xike Xie

Publikation: Bidrag til bog/antologi/rapportKonferenceartikel i proceedingpeer review


In recent years, real-time processing and analytics systems for big data–in the context of Business Intelligence (BI)–have received a growing attention. The traditional BI platforms that perform regular updates on daily, weekly or monthly basis are no longer adequate to satisfy the fast-changing business environments. However, due to the nature of big data, it has become a challenge to achieve the real-time capability using the traditional technologies. The recent distributed computing technology, MapReduce, provides off-the-shelf high scalability that can significantly shorten the processing time for big data; Its open-source implementation such as Hadoop has become the de-facto standard for processing big data, however, Hadoop has the limitation of supporting real-time updates. The improvements in Hadoop for the real-time capability, and the other alternative real-time frameworks have been emerging in recent years. This paper presents a survey of the open source technologies that support big data processing in a real-time/near real-time fashion, including their system architectures and platforms.
TitelIDEAS 14 Proceedings of the 18th International Database Engineering & Applications Symposium
RedaktørerBipin C. Desai
Antal sider6
ForlagAssociation for Computing Machinery
Publikationsdatojul. 2014
ISBN (Elektronisk)978-1-4503-2627-8
StatusUdgivet - jul. 2014


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