Optimizing Query Strategies in Fixed Vertical Partitioned and Distributed Databases and their Application in Semantic Web Databases

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ISBN: 3844060979
ISBN 13: 9783844060973
Autor: Kohler, Jens
Verlag: Shaker Verlag GmbH
Umfang: 217 S., 57 Illustr.
Erscheinungsdatum: 10.08.2018
Auflage: 1/2018
Produktform: Kartoniert
Einband: Kartoniert

Storing data in relational databases has a long history. Such relational databases still build the foundation for various applications throughout all application domains even with todays growing data volumes. Thus, despite a rapid dissemination of In-Memory or NoSQL databases, relational databases will keep their important role, as it is considered not very likely that NoSQL databases will replace them in the near future. Hence, also relational databases are used as a foundation to store huge volumes of data and this is exactly where Cloud Computing o?ers dynamic and scalable capabilities. Renting such technological assets and capabilities from external cloud providers is an interesting approach. As there are still open and unanswered data security and data protection challenges, the usage of especially public Cloud Computing is far behind its expectations. An approach that contributes to the broad dissemination of using especially public clouds is SeDiCo, aframeworkforaSEcure and DI stributed C loud Data stOre. The key concept of this approach is to vertically partition relational database data and store the respective partitions in di?erent databases operated in di?erent clouds. The author of this work firstly proposed this socalled security-by-distribution concept in 2012 and developed and implemented it prototypically. Although these works proved the technological feasibility, the approach still su?ers from severe performance problems when the partitioned and distributed data are accessed. These performance issues are in the focus of this thesis, which aims at investigating, developing and evaluating new ways of accessing those data.

Artikelnummer: 5332883 Kategorie:

Beschreibung

Storing data in relational databases has a long history since Codd defined the relational model and its normal forms in (Codd, 1970). Such relational databases still build the foundation for various applications throughout all application domains even with todays growing data volumes. It is assumed that, despite a rapid dissemination of In-Memory or NoSQL databases, relational databases will keep their important role. Hence, also relational databases are used as a foundation to store huge volumes of data and this is exactly where Cloud Computing offers dynamic and scalable capabilities. Renting such technological assets and capabilities from external cloud providers is an interesting approach. The pay-as-you-go character of these cloud offers, promise the usage of computing assets without large initial investments. In Cloud Computing environments, dedicated services are used for a certain time and are paid only for the respective usage. Moreover, as there are dedicated services, the complexity to integrate and use them is considered lower compared to paradigms like service-oriented architectures. As there are still open data security and data protection challenges, the usage of especially public Cloud Computing is far behind the expectations of e.g. Gartner (Carlton, 2013) and IDC (Gens & Shirer, 2013). Thus in this thesis, data security and data protection challenges for relational databases are addressed with the definition and an implementation of a framework for a SEcure and DI stributed C loud Data StOre, exploiting afixed vertical partitioning and distribution (FVPD) scheme. The main contribution of this work is to show that the proposed framework provides comparable response times to non-partitioned relational databases using cloud infrastructures and contemporary hardware devices.

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