Towards Migration-Free Just-In-Case Data Archival for Future Cloud Data Lakes

Eugenio Marinelli, Yiqing Yan, V. Magnone, Charlotte Dumargne, P. Barbry, T. Heinis, Raja Appuswamy
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引用次数: 0

Abstract

Given the growing adoption of AI, cloud data lakes are facing the need to support cost-effective "just-in-case" data archival over long time periods to meet regulatory compliance requirements. Unfortunately, current media technologies suffer from fundamental issues that will soon, if not already, make cost-effective data archival infeasible. In this paper, we present a vision for redesigning the archival tier of cloud data lakes based on a novel, obsolescence-free storage medium-synthetic DNA. In doing so, we make two contributions: (i) we highlight the challenges in using DNA for data archival and list several open research problems, (ii) we outline OligoArchive-DSM (OA-DSM)-an end-to-end DNA storage pipeline that we are developing to demonstrate the feasibility of our vision.
面向未来云数据湖的免迁移即时数据归档
鉴于人工智能的日益普及,云数据湖正面临着长期支持经济高效的“以防万一”数据存档的需求,以满足法规遵从性要求。不幸的是,当前的媒体技术存在一些基本问题,这些问题很快(如果不是已经)将使具有成本效益的数据存档变得不可行。在本文中,我们提出了一个基于一种新颖的、无过时的存储介质——合成DNA——重新设计云数据湖存档层的愿景。在此过程中,我们做出了两个贡献:(i)我们强调了使用DNA进行数据存档的挑战,并列出了几个开放的研究问题,(ii)我们概述了OligoArchive-DSM (OA-DSM)——我们正在开发的端到端DNA存储管道,以证明我们愿景的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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