NoSQL document data migration strategy in the context of schema evolution

IF 2.7 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Solomiia Fedushko , Roman Malyi , Yuriy Syerov , Pavlo Serdyuk
{"title":"NoSQL document data migration strategy in the context of schema evolution","authors":"Solomiia Fedushko ,&nbsp;Roman Malyi ,&nbsp;Yuriy Syerov ,&nbsp;Pavlo Serdyuk","doi":"10.1016/j.datak.2024.102369","DOIUrl":null,"url":null,"abstract":"<div><div>In Agile development, one approach cannot be chosen and used all the time. Constant updates and strategy changes are necessary. We want to show that combining several migration strategies is better than choosing only one. Also, we emphasize the need to consider the type of schema change. This paper introduces a novel approach designed to optimize the migration process for NoSQL databases. The approach represents a significant advancement in migration strategy planning, providing a quantitative framework to guide decision-making. By incorporating critical factors such as schema changes, database size, the necessity of data in search functionalities, and potential latency issues, the approach comprehensively evaluates the migration feasibility and identifies the optimal migration path. Unlike existing methodologies, this approach adapts to the dynamic nature of NoSQL databases, offering a scalable and flexible approach to migration planning.</div></div>","PeriodicalId":55184,"journal":{"name":"Data & Knowledge Engineering","volume":"154 ","pages":"Article 102369"},"PeriodicalIF":2.7000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data & Knowledge Engineering","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0169023X24000934","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

In Agile development, one approach cannot be chosen and used all the time. Constant updates and strategy changes are necessary. We want to show that combining several migration strategies is better than choosing only one. Also, we emphasize the need to consider the type of schema change. This paper introduces a novel approach designed to optimize the migration process for NoSQL databases. The approach represents a significant advancement in migration strategy planning, providing a quantitative framework to guide decision-making. By incorporating critical factors such as schema changes, database size, the necessity of data in search functionalities, and potential latency issues, the approach comprehensively evaluates the migration feasibility and identifies the optimal migration path. Unlike existing methodologies, this approach adapts to the dynamic nature of NoSQL databases, offering a scalable and flexible approach to migration planning.
模式演进背景下的 NoSQL 文档数据迁移策略
在敏捷开发中,不可能一直选择和使用一种方法。不断更新和改变策略是必要的。我们希望证明,结合几种迁移策略比只选择一种迁移策略更好。此外,我们还强调需要考虑模式变更的类型。本文介绍了一种旨在优化 NoSQL 数据库迁移过程的新方法。该方法为指导决策提供了一个量化框架,是迁移策略规划领域的一大进步。通过纳入模式变更、数据库大小、搜索功能中数据的必要性和潜在延迟问题等关键因素,该方法全面评估了迁移的可行性,并确定了最佳迁移路径。与现有方法不同的是,这种方法适应 NoSQL 数据库的动态特性,为迁移规划提供了一种可扩展的灵活方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Data & Knowledge Engineering
Data & Knowledge Engineering 工程技术-计算机:人工智能
CiteScore
5.00
自引率
0.00%
发文量
66
审稿时长
6 months
期刊介绍: Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKE reaches a world-wide audience of researchers, designers, managers and users. The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these systems.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信