The challenges of global-scale data management

Faisal Nawab, Divyakant Agrawal, Amr El Abbadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Global-scale data management (GSDM) empowers systems by providing higher levels of fault-tolerance, read availability, and efficiency in utilizing cloud resources. This has led to the emergence of global-scale data management and event processing. However, the Wide-Area Network (WAN) latency separating data is orders of magnitude larger than conventional network latencies, and this requires a reevaluation of many of the traditional design trade-offs of data management systems. Therefore, data management problems must be revisited to account for the new design space. In this tutorial we survey recent developments in GSDM focusing on identifying fundamental challenges and advancements in addition to open research opportunities.

Original languageEnglish
Title of host publicationSIGMOD 2016 - Proceedings of the 2016 International Conference on Management of Data
PublisherAssociation for Computing Machinery
Pages2223-2227
Number of pages5
ISBN (Electronic)9781450335317
DOIs
Publication statusPublished - 26 Jun 2016
Event2016 ACM SIGMOD International Conference on Management of Data, SIGMOD 2016 - San Francisco, United States
Duration: 26 Jun 20161 Jul 2016

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
Volume26-June-2016
ISSN (Print)0730-8078

Other

Other2016 ACM SIGMOD International Conference on Management of Data, SIGMOD 2016
CountryUnited States
CitySan Francisco
Period26/6/161/7/16

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ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

Nawab, F., Agrawal, D., & El Abbadi, A. (2016). The challenges of global-scale data management. In SIGMOD 2016 - Proceedings of the 2016 International Conference on Management of Data (pp. 2223-2227). (Proceedings of the ACM SIGMOD International Conference on Management of Data; Vol. 26-June-2016). Association for Computing Machinery. https://doi.org/10.1145/2882903.2912571