Abstract
In recent years, real-time processing and analytics systems for big data-in the context of Business Intelligence (Bl)-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. How-ever, 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.
Originalsprog | Engelsk |
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Titel | ACM International Conference Proceeding Series |
Antal sider | 6 |
Forlag | Association for Computing Machinery |
Publikationsdato | 2014 |
Sider | 356-361 |
ISBN (Trykt) | 978-1-4503-2627-8 |
DOI | |
Status | Udgivet - 2014 |
Begivenhed | 18th International Database Engineering & Applications Symposium - Porto, Portugal Varighed: 7 jul. 2014 → 9 jul. 2014 |
Konference
Konference | 18th International Database Engineering & Applications Symposium |
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Land/Område | Portugal |
By | Porto |
Periode | 07/07/2014 → 09/07/2014 |