Extensibility and Data Sharing in evolving multi-tenant databases

Aulbach, Stefan; Seibold, Michael; Jacobs, Dean; Kemper, Alfons

doi:10.1109/icde.2011.5767872

Cited by 31 publications

(13 citation statements)

References 12 publications

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“…However, the performance overhead caused by VMs (paging [22], contention [30], OS redundancy [17]) may be too expensive for the more data-intensive workloads considered in this paper. Thus, a number of frameworks for building native multi-tenant applications have also been proposed [6], [13], [34].…”

Section: Related Workmentioning

confidence: 99%

Towards Multi-tenant Performance SLOs

Lang

Shankar

Patel

et al. 2012

2012 IEEE 28th International Conference on Data Engineering

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As traditional and mission-critical relational database workloads migrate to the cloud in the form of Databaseas-a-Service (DaaS), there is an increasing motivation to provide performance goals in Service Level Objectives (SLOs). Providing such performance goals is challenging for DaaS providers as they must balance the performance that they can deliver to tenants and the data center's operating costs. In general, aggressively aggregating tenants on each server reduces the operating costs but degrades performance for the tenants, and vice versa. In this paper, we present a framework that takes as input the tenant workloads, their performance SLOs, and the server hardware that is available to the DaaS provider, and outputs a costeffective recipe that specifies how much hardware to provision and how to schedule the tenants on each hardware resource. We evaluate our method and show that it produces effective solutions that can reduce the costs for the DaaS provider while meeting performance goals.

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Section: Related Workmentioning

confidence: 99%

Towards Multi-tenant Performance SLOs

Lang

Shankar

Patel

et al. 2012

2012 IEEE 28th International Conference on Data Engineering

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“…The algorithm starts by generating a middle point r mid (line 6) between the two points (r high , r low ) bounding the search line. Initially, r high is the point where the perpendicular line intersects the upper or the right side of the search region, and r low is the point where the perpendicular line intersects with either x-or y-axis.…”

Section: Scenario Ii: What Can a $Z Cost Budget Buy?mentioning

confidence: 99%

“…A data sharing effort in the cloud is the FLEXSCHEME [6], where multiple versions of shared schema are maintained in the cloud, with the focus on enabling evolution of shared schema used by multiple tenants. Orchestra [25] casts data sharing as a data integration problem, where reconciling the difference in schema, formats, and trust between peers is achieved using provenance information associated with the tuples.…”

Section: Related Workmentioning

confidence: 99%

Cost exploration of data sharings in the cloud

Al-Kiswany¹,

Hacıgümüş

Liu

et al. 2013

Proceedings of the 16th International Conference on Extending Database Technology

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Enabling data sharing among mobile apps hosted in the same cloud infrastructure can provide a competitive advantage to the mobile apps by giving them access to rich information as well as increasing the revenue for the cloud provider. We introduce a costing tool that allows application owners (i.e., consumers) and the cloud service provider to assess the cost of a desired data sharing. The costing tool enables the consumers to effectively explore the cost space by choosing between alternative configurations of varying data qualities, specified by the staleness and the accuracy of the data sharing. In other words, staleness and accuracy requirements on the data sharing are used as levers for controlling costs. These capabilities are implemented in a What-if analysis tool, which has been integrated with a large data-sharing platform. We conducted extensive experiments on the integrated platform with a sharing ecosystem created around Twitter data and show the effectiveness of the results produced by the What-if tool.

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“…Based on the extension table, frequently accessed extension fields are removed into basic table [8]. A next-generation multi-tenant DBMS should provide explicit support for Extensibility, Data Sharing and Evolution [9]. They propose FLEXSCHEME which captures all three aspects in one integrated mode.…”

Section: Cet: Clustering Extensionmentioning

confidence: 99%