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Towards Migration-Free "Just-in-Case" Data Archival for Future Cloud Data Lakes Using Synthetic DNA
Eugenio Marinelli, Yiqing Yan, Virginie Magnone, Charlotte Dumargne, Pascal Barbry, Thomas Heinis, Raja Appuswamy

Towards Migration-Free "Just-in-Case" Data Archival for Future Cloud Data Lakes Using Synthetic DNA

Science & Mathematics Published 2023 Verification Pending

Overview & Synopsis

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.

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Document Information

Document Title Towards Migration-Free "Just-in-Case" Data Archival for Future Cloud Data Lakes Using Synthetic DNA
Author / Organization Eugenio Marinelli, Yiqing Yan, Virginie Magnone, Charlotte Dumargne, Pascal Barbry, Thomas Heinis, Raja Appuswamy
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2023
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-188727
Original Source Link Visit Source Page on hal.science »