Disaggregated Database Systems

Jianguo Wang, Qizhen Zhang
{"title":"Disaggregated Database Systems","authors":"Jianguo Wang, Qizhen Zhang","doi":"10.1145/3555041.3589403","DOIUrl":null,"url":null,"abstract":"Disaggregated database systems achieve unprecedented excellence in elasticity and resource utilization at the cloud scale and have gained great momentum from both industry and academia recently. Such systems are developed in response to the emerging trend of disaggregated data centers where resources are physically separated and connected through fast data center networks. Database management systems have been traditionally built based on monolithic architectures, so disaggregation fundamentally challenges the designs. On the other hand, disaggregation offers benefits like independent scaling of compute, memory, and storage. Nonetheless, there is a lack of systematic investigation into new research challenges and opportunities in recent disaggregated database systems. To provide database researchers and practitioners with insights into different forms of resource disaggregation, we take a snapshot of state-of-the-art disaggregated database systems and related techniques and present an in-depth tutorial. The primary goal is to better understand the enabling techniques and characteristics of resource disaggregation and its implications for next-generation database systems. To that end, we survey recent work on storage disaggregation, which separates secondary storage devices (e.g., SSDs) from compute servers and is widely deployed in current cloud data centers, and memory disaggregation, which further splits compute and memory with Remote Direct Memory Access (RDMA) and is driving the transformation of clouds. In addition, we mention two techniques that bring novel perspectives to the above two paradigms: persistent memory and Compute Express Link (CXL). Finally, we identify several directions that shed light on the future development of disaggregated database systems.","PeriodicalId":161812,"journal":{"name":"Companion of the 2023 International Conference on Management of Data","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Companion of the 2023 International Conference on Management of Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3555041.3589403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Disaggregated database systems achieve unprecedented excellence in elasticity and resource utilization at the cloud scale and have gained great momentum from both industry and academia recently. Such systems are developed in response to the emerging trend of disaggregated data centers where resources are physically separated and connected through fast data center networks. Database management systems have been traditionally built based on monolithic architectures, so disaggregation fundamentally challenges the designs. On the other hand, disaggregation offers benefits like independent scaling of compute, memory, and storage. Nonetheless, there is a lack of systematic investigation into new research challenges and opportunities in recent disaggregated database systems. To provide database researchers and practitioners with insights into different forms of resource disaggregation, we take a snapshot of state-of-the-art disaggregated database systems and related techniques and present an in-depth tutorial. The primary goal is to better understand the enabling techniques and characteristics of resource disaggregation and its implications for next-generation database systems. To that end, we survey recent work on storage disaggregation, which separates secondary storage devices (e.g., SSDs) from compute servers and is widely deployed in current cloud data centers, and memory disaggregation, which further splits compute and memory with Remote Direct Memory Access (RDMA) and is driving the transformation of clouds. In addition, we mention two techniques that bring novel perspectives to the above two paradigms: persistent memory and Compute Express Link (CXL). Finally, we identify several directions that shed light on the future development of disaggregated database systems.
分类数据库系统
在云规模下,分解数据库系统在弹性和资源利用率方面取得了前所未有的卓越成就,近年来在工业界和学术界都获得了很大的发展势头。这种系统是为了响应分解数据中心的新趋势而开发的,即资源在物理上分离,并通过快速的数据中心网络连接。数据库管理系统传统上是基于单体架构构建的,因此分解从根本上挑战了设计。另一方面,分解提供了一些好处,比如计算、内存和存储的独立扩展。然而,在最近的分类数据库系统中,缺乏对新的研究挑战和机会的系统调查。为了给数据库研究人员和从业者提供对不同形式的资源分解的见解,我们对最先进的分解数据库系统和相关技术进行了快照,并提供了深入的教程。主要目标是更好地理解资源分解的启用技术和特征及其对下一代数据库系统的影响。为此,我们调查了最近在存储分解和内存分解方面的工作,存储分解将二级存储设备(例如ssd)从计算服务器中分离出来,并广泛部署在当前的云数据中心中,内存分解通过远程直接内存访问(RDMA)进一步分离计算和内存,并推动了云的转型。此外,我们还提到了两种技术,它们为上述两种范式带来了新的视角:持久内存和Compute Express Link (CXL)。最后,我们确定了几个方向,阐明了分解数据库系统的未来发展。
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
自引率
0.00%
发文量
0
×
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:604180095
Book学术官方微信