Abstract
The challenge of building consistent, available, and scalable data management systems capable of serving petabytes of data for millions of users has confronted the data management research community as well as large internet enterprises. Current proposed solutions to scalable data management, driven primarily by prevalent application requirements, limit consistent access to only the granularity of single objects, rows, or keys, thereby trading off consistency for high scalability and availability. But the growing popularity of “cloud computing”, the resulting shift of a large number of internet applications to the cloud, and the quest towards providing data management services in the cloud, has opened up the challenge for designing data management systems that provide consistency guarantees at a granularity larger than single rows and keys. In this paper, we analyze the design choices that allowed modern scalable data management systems to achieve orders of magnitude higher levels of scalability compared to traditional databases. With this understanding, we highlight some design principles for systems providing scalable and consistent data management as a service in the cloud.
This work is partially funded by NSF grant NSF IIS-0847925.
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Agrawal, D., El Abbadi, A., Antony, S., Das, S. (2010). Data Management Challenges in Cloud Computing Infrastructures. In: Kikuchi, S., Sachdeva, S., Bhalla, S. (eds) Databases in Networked Information Systems. DNIS 2010. Lecture Notes in Computer Science, vol 5999. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12038-1_1
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DOI: https://doi.org/10.1007/978-3-642-12038-1_1
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