iCBS: incremental cost-based scheduling under piecewise linear SLAs
Proceedings of the VLDB Endowment
Data management research at NEC labs
ACM SIGMOD Record
Performance evaluation of scheduling algorithms for database services with soft and hard SLAs
Proceedings of the second international workshop on Data intensive computing in the clouds
Microsharding: a declarative approach to support elastic OLTP workloads
ACM SIGOPS Operating Systems Review
Partiqle: an elastic SQL engine over key-value stores
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
SWAT: a lightweight load balancing method for multitenant databases
Proceedings of the 16th International Conference on Extending Database Technology
A platform for seamless context transfers in the mobile cloud
Proceedings of the 12th International ACM Workshop on Data Engineering for Wireless and Mobile Acess
Proceedings of the First International Conference on Security of Internet of Things
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We present a data management platform in the cloud, CloudDB. The guiding principle of CloudDB’s design is establishing data independence for the applications that need to use diverse underlying data stores that are optimized for varying workload needs and characteristics. The applications should not have to be aware of the physical organization of the data and how the data is accessed. Ideally, an application only needs a logical specification of the data access layer and the data access requests are handled in a declarative way. CloudDB hosts variety of specialized databases that deliver high performance, scalability, and cost efficiency for varying application needs. CloudDB’s API layer is designed in such a way to give data independence to the higher level applications. The goal is to let the clients use just a simple, standard, and uniform language API to access data management functions as a service.