Evaluating dotted version vectors in Riak

Bibliographic Details
Main Author: Gonçalves, Ricardo Jorge Tomé
Publication Date: 2011
Other Authors: Almeida, Paulo Sérgio, Baquero, Carlos, Fonte, Victor, Preguiça, Nuno
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/1822/36123
Summary: The NoSQL movement is rapidly increasing in importance, acceptance and usage in major (web) applications, that need the partition-tolerance and availability of the CAP theorem for scalability purposes, thus sacrificing the consistency side. With this approach, paradigms such as Eventual Consistency became more widespread. An eventual consistent system must handle data divergence and conflicts, that have to be carefully accounted for. Some systems have tried to use classic Version Vectors (VV) to track causality, but these reveal either scalability problems or loss of accuracy (when pruning is used to prevent vector growth). Dotted Version Vectors (DVV) is a novel mechanism for dealing with data versioning in eventual consistent systems, that allows both accurate causality tracking and scalability both in the number of clients and servers, while limiting vector size to replication degree. In this paper we describe briefly the challenges faced when incorporating DVV in Riak (a distributed key-value store), evaluate its behavior and performance, and discuss the advantages and disadvantages of this specific implementation.
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spelling Evaluating dotted version vectors in RiakDatabasesNoSQLRiakEventual consistencyLogical clocksScalabilityThe NoSQL movement is rapidly increasing in importance, acceptance and usage in major (web) applications, that need the partition-tolerance and availability of the CAP theorem for scalability purposes, thus sacrificing the consistency side. With this approach, paradigms such as Eventual Consistency became more widespread. An eventual consistent system must handle data divergence and conflicts, that have to be carefully accounted for. Some systems have tried to use classic Version Vectors (VV) to track causality, but these reveal either scalability problems or loss of accuracy (when pruning is used to prevent vector growth). Dotted Version Vectors (DVV) is a novel mechanism for dealing with data versioning in eventual consistent systems, that allows both accurate causality tracking and scalability both in the number of clients and servers, while limiting vector size to replication degree. In this paper we describe briefly the challenges faced when incorporating DVV in Riak (a distributed key-value store), evaluate its behavior and performance, and discuss the advantages and disadvantages of this specific implementation.Universidade do MinhoGonçalves, Ricardo Jorge ToméAlmeida, Paulo SérgioBaquero, CarlosFonte, VictorPreguiça, Nuno20112011-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/36123eng10.1.1.307.3327info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T06:03:27Zoai:repositorium.sdum.uminho.pt:1822/36123Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T15:39:30.134721Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Evaluating dotted version vectors in Riak
title Evaluating dotted version vectors in Riak
spellingShingle Evaluating dotted version vectors in Riak
Gonçalves, Ricardo Jorge Tomé
Databases
NoSQL
Riak
Eventual consistency
Logical clocks
Scalability
title_short Evaluating dotted version vectors in Riak
title_full Evaluating dotted version vectors in Riak
title_fullStr Evaluating dotted version vectors in Riak
title_full_unstemmed Evaluating dotted version vectors in Riak
title_sort Evaluating dotted version vectors in Riak
author Gonçalves, Ricardo Jorge Tomé
author_facet Gonçalves, Ricardo Jorge Tomé
Almeida, Paulo Sérgio
Baquero, Carlos
Fonte, Victor
Preguiça, Nuno
author_role author
author2 Almeida, Paulo Sérgio
Baquero, Carlos
Fonte, Victor
Preguiça, Nuno
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Gonçalves, Ricardo Jorge Tomé
Almeida, Paulo Sérgio
Baquero, Carlos
Fonte, Victor
Preguiça, Nuno
dc.subject.por.fl_str_mv Databases
NoSQL
Riak
Eventual consistency
Logical clocks
Scalability
topic Databases
NoSQL
Riak
Eventual consistency
Logical clocks
Scalability
description The NoSQL movement is rapidly increasing in importance, acceptance and usage in major (web) applications, that need the partition-tolerance and availability of the CAP theorem for scalability purposes, thus sacrificing the consistency side. With this approach, paradigms such as Eventual Consistency became more widespread. An eventual consistent system must handle data divergence and conflicts, that have to be carefully accounted for. Some systems have tried to use classic Version Vectors (VV) to track causality, but these reveal either scalability problems or loss of accuracy (when pruning is used to prevent vector growth). Dotted Version Vectors (DVV) is a novel mechanism for dealing with data versioning in eventual consistent systems, that allows both accurate causality tracking and scalability both in the number of clients and servers, while limiting vector size to replication degree. In this paper we describe briefly the challenges faced when incorporating DVV in Riak (a distributed key-value store), evaluate its behavior and performance, and discuss the advantages and disadvantages of this specific implementation.
publishDate 2011
dc.date.none.fl_str_mv 2011
2011-01-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/36123
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dc.language.iso.fl_str_mv eng
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dc.relation.none.fl_str_mv 10.1.1.307.3327
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