Survey of Large-Scale Data Management Systems for Big Data Applications
Today, data is flowing into various organizations at an unprecedented scale. The ability to scale out for processing an enhanced workload has become an important factor for the proliferation and popularization of database systems. Big data applications demand and consequently lead to the development...
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| Published in: | Journal of computer science and technology Vol. 30; no. 1; pp. 163 - 183 |
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| Main Author: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
Boston
Springer US
2015
Springer Nature B.V |
| Subjects: | |
| Online Access: | Get full text |
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| Summary: | Today, data is flowing into various organizations at an unprecedented scale. The ability to scale out for processing an enhanced workload has become an important factor for the proliferation and popularization of database systems. Big data applications demand and consequently lead to the developments of diverse large-scale data management systems in different organizations, ranging from traditional database vendors to new emerging Internet-based enterprises. In this survey, we investigate, characterize, and analyze the large-scale data management systems in depth and develop comprehensive taxonomies for various critical aspects covering the data model, the system architecture, and the consistency model. We map the prevailing highly scalable data management systems to the proposed taxonomies, not only to classify the common techniques but also to provide a basis for analyzing current system scalability limitations. To overcome these limitations, we predicate and highlight the possible principles that future efforts need to be undertaken for the next generation large-scale data management systems. |
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| Bibliography: | data model, system architecture, consistency model, scalability Today, data is flowing into various organizations at an unprecedented scale. The ability to scale out for processing an enhanced workload has become an important factor for the proliferation and popularization of database systems. Big data applications demand and consequently lead to the developments of diverse large-scale data management systems in different organizations, ranging from traditional database vendors to new emerging Internet-based enterprises. In this survey, we investigate, characterize, and analyze the large-scale data management systems in depth and develop comprehensive taxonomies for various critical aspects covering the data model, the system architecture, and the consistency model. We map the prevailing highly scalable data management systems to the proposed taxonomies, not only to classify the common techniques but also to provide a basis for analyzing current system scalability limitations. To overcome these limitations, we predicate and highlight the possible principles that future efforts need to be undertaken for the next generation large-scale data management systems. 11-2296/TP ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1000-9000 1860-4749 |
| DOI: | 10.1007/s11390-015-1511-8 |