Survey of Real-time Processing Systems for Big Data

Xiufeng Liu, Nadeem Iftikhar, Xike Xie

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-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.
Original languageEnglish
Title of host publicationProceedings of the 18th International Database Engineering and Applications Symposium
Number of pages6
PublisherAssociation for Computing Machinery
Publication date2014
ISBN (Print)978-1-4503-2627-8
Publication statusPublished - 2014
Externally publishedYes
Event18th International Database Engineering and Applications Symposium - Porto, Portugal
Duration: 7 Jul 20149 Jul 2014
Conference number: 18


Conference18th International Database Engineering and Applications Symposium

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