Benchmarking Database Performance in a Virtual Environment

Bose, Sharada; Mishra, Priti; Sethuraman, Priya; Taheri, Reza

doi:10.1007/978-3-642-10424-4_13

Cited by 14 publications

(8 citation statements)

References 9 publications

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“…Most existing work agrees that virtualization causes only a small overhead for database systems both for transactional and analytical workloads [8,2,5,1,4,9].…”

Section: Related Workmentioning

confidence: 99%

High-Performance Main-Memory Database Systems and Modern Virtualization

Mühlbauer

Rödiger

Kipf

et al. 2015

Proceedings of the Fourth Workshop on Data Analytics in the Cloud

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Virtualization owes its popularity mainly to its ability to consolidate software systems from many servers into a single server without sacrificing the desirable isolation between applications. This not only reduces the total cost of ownership, but also enables rapid deployment of complex software and application-agnostic live migration between servers for load balancing, high-availability, and fault-tolerance.However, virtualization is no free lunch. To achieve isolation, virtualization environments need to add an additional layer of abstraction between the bare metal hardware and the application. This inevitably introduces a performance overhead. High-performance main-memory database systems are specifically susceptible to additional software abstractions as they are closely optimized and tuned for the underlying hardware. In this work, we analyze in detail how much overhead modern virtualization options introduce for high-performance main-memory database systems. We evaluate and compare the performance of HyPer and MonetDB under three modern virtualization environments for analytical as well as transactional workloads. Our experiments show that the overhead depends on the system and virtualization environment being used. We further show that mainmemory database systems can be efficiently deployed in virtualized cloud environments such as the Google Compute Engine and that "friendship" between modern virtualization and main-memory database systems is indeed possible.

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“…Most existing work agrees that virtualization causes only a small overhead for database systems both for transactional and analytical workloads [8,2,5,1,4,9].…”

Section: Related Workmentioning

confidence: 99%

High-Performance Main-Memory Database Systems and Modern Virtualization

Mühlbauer

Rödiger

Kipf

et al. 2015

Proceedings of the Fourth Workshop on Data Analytics in the Cloud

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“…Complexity-Complexity is defined as the degree to which Cloud based services is perceived as being comparatively complex to understand and use by SMEs. [18][19][20] [21]…”

Section: (A) Diffusion Of Innovation Theory (Doi) Frameworkmentioning

confidence: 99%

A Study to Explore the Key Factors Impacting on Cloud Based Service Adoption in Indian SMEs

Gide

Sandu

2015

2015 IEEE 12th International Conference on E-Business Engineering

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This paper discusses the factors influencing Indian Small and Medium Enterprises' (SMEs) adoption of Cloud based services. This research, through an extensive literature review, analyzes the current situation, benefits, and challenges of Cloud based services adoption for Indian SMEs. It identifies and confirms the key factors (e.g., cost reduction, relative advantage, security, regulatory support, firm size, top management support, technological readiness) that determine the adoption of Cloud based services by Indian SMEs, based on secondary research. The target population for this study is SMEs in India that are using or considering using Cloud based services, regardless of the field or industry. The theoretical basis for this study is the Diffusion of Innovation (DOI) theory, and Technology Organization andEnvironment (TOE) theory. These two technology adoption theories present a solid theoretical framework on which this study is based. This paper provides an understanding of the extent to which innovation characteristics, technology context, organizational context, and environmental context influence the decision of Indian SMEs to adopt Cloud based services.

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“…In a recent paper [10], the performance of relational database systems running on top of virtual machines has been studied. Bose et al [4] present performance results from experiments running TPC database workloads on top of virtual machines, and make the case for a database benchmark on top of virtual machines. The follow-up work [14] presents a high-level overview of TPC-V, a benchmark designed for database workloads running in virtualized environments.…”

Section: Related Workmentioning

confidence: 99%

When Free Is Not Really Free: What Does It Cost to Run a Database Workload in the Cloud?

Floratou

Patel

Lang

et al. 2012

Topics in Performance Evaluation, Measurement and Characterization

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Abstract. The current computing trend towards cloud-based Databaseas-a-Service (DaaS) as an alternative to traditional on-site relational database management systems (RDBMSs) has largely been driven by the perceived simplicity and cost-effectiveness of migrating to a DaaS. However, customers that are attracted to these DaaS alternatives may find that the range of different services and pricing options available to them add an unexpected level of complexity to their decision making. Cloud service pricing models are typically 'pay-as-you-go' in which the customer is charged based on resource usage such as CPU and memory utilization. Thus, customers considering different DaaS options must take into account how the performance and efficiency of the DaaS will ultimately impact their monthly bill. In this paper, we show that the current DaaS model can produce unpleasant surprises -for example, the case study that we present in this paper illustrates a scenario in which a DaaS service powered by a DBMS that has a lower hourly rate actually costs more to the end user than a DaaS service that is powered by another DBMS that charges a higher hourly rate. Thus, what we need is a method for the end-user to get an accurate estimate of the true costs that will be incurred without worrying about the nuances of how the DaaS operates. One potential solution to this problem is for DaaS providers to offer a new service called Benchmark as a Service (BaaS) where in the user provides the parameters of their workload and SLA requirements, and get a price quote.

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Benchmarking Database Performance in a Virtual Environment

Cited by 14 publications

References 9 publications

High-Performance Main-Memory Database Systems and Modern Virtualization

High-Performance Main-Memory Database Systems and Modern Virtualization

A Study to Explore the Key Factors Impacting on Cloud Based Service Adoption in Indian SMEs

When Free Is Not Really Free: What Does It Cost to Run a Database Workload in the Cloud?

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