poster

On the elasticity of NoSQL databases over cloud management platforms

Authors:

Ioannis Konstantinou,

Evangelos Angelou,

Christina Boumpouka,

Dimitrios Tsoumakos,

Nectarios KozirisAuthors Info & Claims

CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management

Pages 2385 - 2388

https://doi.org/10.1145/2063576.2063973

Published: 24 October 2011 Publication History

Abstract

NoSQL databases focus on analytical processing of large scale datasets, offering increased scalability over commodity hardware. One of their strongest features is elasticity, which allows for fairly portioned premiums and high-quality performance and directly applies to the philosophy of a cloud-based platform. Yet, the process of adaptive expansion and contraction of resources usually involves a lot of manual effort during cluster configuration. To date, there exists no comparative study to quantify this cost and measure the efficacy of NoSQL engines that offer this feature over a cloud provider. In this work, we present a cloud-enabled framework for adaptive monitoring of NoSQL systems. We perform a study of the elasticity feature on some of the most popular NoSQL databases over an open-source cloud platform. Based on these measurements, we finally present a prototype implementation of a decision making system that enables automatic elastic operations of any NoSQL engine based on administrator or application-specified constraints.

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Digital Library

Cited By

Copik MCalotoiu AZhou PTaranov KHoefler TMencagli GDazzi PLowenthal DBadia R(2024)FaaSKeeper: Learning from Building Serverless Services with ZooKeeper as an ExampleProceedings of the 33rd International Symposium on High-Performance Parallel and Distributed Computing10.1145/3625549.3658661(94-108)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3625549.3658661
Demirezen MNavruz T(2023)Performance Analysis of Lambda Architecture-Based Big-Data Systems on Air/Ground Surveillance Application with ADS-B DataSensors10.3390/s2317758023:17(7580)Online publication date: 31-Aug-2023
https://doi.org/10.3390/s23177580
von Buelow MTausch RSchurig MKnauthe VWirth TGuthe SSantos PFellner D(2022)Depth-of-Field Segmentation for Near-lossless Image Compression and 3D ReconstructionJournal on Computing and Cultural Heritage 10.1145/350092415:3(1-16)Online publication date: 16-Sep-2022
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Index Terms

On the elasticity of NoSQL databases over cloud management platforms
1. Information systems
  1. Information retrieval
    1. Search engine architectures and scalability
      1. Distributed retrieval
      2. Peer-to-peer retrieval
  2. Information storage systems
    1. Storage architectures
      1. Distributed storage

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Published In

cover image ACM Conferences

CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management

October 2011

2712 pages

ISBN:9781450307178

DOI:10.1145/2063576

Editors:
Bettina Berendt,
Arjen de Vries,
Wenfei Fan,
Craig Macdonald
University of Glasgow, UK
,
Iadh Ounis
University of Glasgow, UK
,
Ian Ruthven
University of Strathclyde, UK

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 24 October 2011

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CIKM '11: International Conference on Information and Knowledge Management

October 24 - 28, 2011

Glasgow, Scotland, UK

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

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https://dl.acm.org/doi/10.1145/3625549.3658661
Demirezen MNavruz T(2023)Performance Analysis of Lambda Architecture-Based Big-Data Systems on Air/Ground Surveillance Application with ADS-B DataSensors10.3390/s2317758023:17(7580)Online publication date: 31-Aug-2023
https://doi.org/10.3390/s23177580
von Buelow MTausch RSchurig MKnauthe VWirth TGuthe SSantos PFellner D(2022)Depth-of-Field Segmentation for Near-lossless Image Compression and 3D ReconstructionJournal on Computing and Cultural Heritage 10.1145/350092415:3(1-16)Online publication date: 16-Sep-2022
https://dl.acm.org/doi/10.1145/3500924
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