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The Case for Object Databases in Cloud Data Management

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Objects and Databases (ICOODB 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6348))

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Abstract

With the emergence of cloud computing, new data management requirements have surfaced. Currently, these challenges are studied exclusively in the setting of relational databases. We believe that there exist strong indicators that the full potential of cloud computing data management can only be leveraged by exploiting object database technologies. Object databases are a popular choice for analytical data management applications which are predicted to profit most from cloud computing. Furthermore, objects and relationships might be useful units to model and implement data partitions, while, at the same time, helping to reduce join processing. Finally, the service-oriented view taken by cloud computing is in its nature a close match to object models. In this position paper, we examine the challenges of cloud computing data management and show opportunities for object database technologies based on these requirements.

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Author information

Authors and Affiliations

  1. Dipartimento di Elettronica e Informazione, Politecnico di Milano, P.za Leonardo Da Vinci, 32, I-20133, Milano, Italy

    Michael Grossniklaus

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  1. Michael Grossniklaus
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Editors and Affiliations

  1. School of Computer Science, University of St Andrews, Jack Cole Building, North Haugh, KY16 9SX, St Andrews, UK

    Alan Dearle

  2. Institute of Computer Science, Johann Wolfgang Goethe-University, Robert Mayer-Str. 10, 60325, Frankfurt/Main, Germany

    Roberto V. Zicari

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Grossniklaus, M. (2010). The Case for Object Databases in Cloud Data Management. In: Dearle, A., Zicari, R.V. (eds) Objects and Databases. ICOODB 2010. Lecture Notes in Computer Science, vol 6348. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16092-9_6

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  • DOI: https://doi.org/10.1007/978-3-642-16092-9_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16091-2

  • Online ISBN: 978-3-642-16092-9

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