Private Table Database Virtualization for DBaaS

Kiefer, Tim; Lehner, Wolfgang

doi:10.1109/ucc.2011.52

Cited by 16 publications

(10 citation statements)

References 3 publications

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“…Table 2 shows the results of the comparative analysis of the collaboration of the system and this paper Big data processing collaboration system for efficient processing of data in the business environment of the company. When integrating the data in an environment that is dispersed in both the systems, and overcomes the heterogeneity using standardized, an integrated work environment to minimize the effects of local system construction [6] [7]. XMDR-DAI-based collaboration system, while the distributed processing capabilities for sharing data, the proposed system, a large-scale data, not only in the region of the local system, using the cloud also function in a mobile environment, data collect, it is possible to save and purified.…”

Section: Figure 7 Collaboration System Workflowmentioning

confidence: 99%

The Design of Collaboration System for Data Sharing In the Mobile Cloud Environment

Kim¹,

Lee²,

Jung³

2016

International journal of advanced smart convergence

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Section: Figure 7 Collaboration System Workflowmentioning

confidence: 99%

The Design of Collaboration System for Data Sharing In the Mobile Cloud Environment

Kim¹,

Lee²,

Jung³

2016

International journal of advanced smart convergence

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“…Therefore DBaaS is characterized that they provide an environment that can be integrated efficiently database. And is possible efficient data sharing environment integrated into data compatibility [12]. Therefore, in the groupware environment that is integrated on the basis of DBaaS, the overall service of the database, it will provide a solution between enterprises and companies [8].…”

Section: Dbaas(database As a Service)mentioning

confidence: 99%

The Design of Data Hub System for Integration of Group In the Cloud Environment

Kim¹,

Lee²,

Jung³

2015

International journal of advanced smart convergence

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For a recent most companies to make efficient business management, we are using a groupware service of integrated information system of the entire group. Groupware service integrates the cooperation in excellent synergy and duplicates has been business functions of the business, through the improvement of multi-purpose business processing capacity, there is an advantage of reduced operating costs. However, if the parent company and subsidiary, or to handle common tasks such information agency, which may cause differences in the format of the data passed in the case of a need to provide a document. Therefore, in this paper, in order to solve the heterogeneity problem in data between groups, the data system of the hub base of the cloud is provided. The proposed system is intended to improve the groupware environment including the interoperability of integrated standardized environmental data sharing service.

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“…There is still a huge number of commercial applications and systems that store data in relational databases . One important class of queries performed in such databases is online analytical processing (OLAP) queries that usually access large amounts of data and are very time‐consuming.…”

Section: Introductionmentioning

confidence: 99%

“…In many organizations that make use of PDBMSs, there is a dedicated multiprocessor machine for the database server, or even a computer cluster depending on the processing demand . However, these machines and clusters may be quite expensive and are commonly overdimensioned for peak load and may be underutilized most of the time.…”

Section: Introductionmentioning

confidence: 99%

OLAP parallel query processing in clouds with C‐ParGRES

Ribeiro

Lima

Oliveira

2019

Concurrency and Computation

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Summary The advent of big data technologies has changed the way many companies manage their data. Several companies moved their data to the cloud using the concept of database‐as‐a‐service (DBaaS). Moving databases to the cloud presents several challenges related to flexible and scalable management of data. Although some of these companies migrated to NoSQL databases, most still rely on relational databases in the cloud to manage data, especially data that is critical to the decision making process. Online analytical processing (OLAP) queries take a long time to be processed, thus demanding high‐performance capabilities from their associated database systems to get results in a feasible time. In this article, we propose a middleware solution that can be deployed in any cloud provider, named C‐ParGRES, which explores database replication and interquery and intraquery parallelism to efficiently support OLAP queries in the cloud. C‐ParGRES is an extension of ParGRES, an open‐source database cluster middleware for high‐performance OLAP query processing in clusters. C‐ParGRES exploits cloud capabilities such as on‐demand resource provisioning and elasticity. In addition, C‐ParGRES can create multiple and independent virtual clusters for different database and users. We evaluate C‐ParGRES with two real‐world OLAP applications, both from the Brazilian Institute of Geography and Statistics. Results show that C‐ParGRES is a cost‐effective solution for OLAP query processing in the cloud.

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Private Table Database Virtualization for DBaaS

Cited by 16 publications

References 3 publications

The Design of Collaboration System for Data Sharing In the Mobile Cloud Environment

The Design of Collaboration System for Data Sharing In the Mobile Cloud Environment

The Design of Data Hub System for Integration of Group In the Cloud Environment

OLAP parallel query processing in clouds with C‐ParGRES

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