Qian Lin, Kaiyuan Yang, Tien Tuan Anh Dinh, Qingchao Cai, Gang Chen, B. Ooi, Pingcheng Ruan, Sheng Wang, Zhongle Xie, Meihui Zhang, Olafs Vandans
{"title":"ForkBase: Immutable, Tamper-evident Storage Substrate for Branchable Applications","authors":"Qian Lin, Kaiyuan Yang, Tien Tuan Anh Dinh, Qingchao Cai, Gang Chen, B. Ooi, Pingcheng Ruan, Sheng Wang, Zhongle Xie, Meihui Zhang, Olafs Vandans","doi":"10.1109/ICDE48307.2020.00153","DOIUrl":null,"url":null,"abstract":"Data collaboration activities typically require systematic or protocol-based coordination to be scalable. Git, an effective enabler for collaborative coding, has been attested for its success in countless projects around the world. Hence, applying the Git philosophy to general data collaboration beyond coding is motivating. We call it Git for data. However, the original Git design handles data at the file granule, which is considered too coarse-grained for many database applications. We argue that Git for data should be co-designed with database systems. To this end, we developed ForkBase to make Git for data practical. ForkBase is a distributed, immutable storage system designed for data version management and data collaborative operation. In this demonstration, we show how ForkBase can greatly facilitate collaborative data management and how its novel data deduplication technique can improve storage efficiency for archiving massive data versions.","PeriodicalId":6709,"journal":{"name":"2020 IEEE 36th International Conference on Data Engineering (ICDE)","volume":"25 1","pages":"1718-1721"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 36th International Conference on Data Engineering (ICDE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE48307.2020.00153","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Data collaboration activities typically require systematic or protocol-based coordination to be scalable. Git, an effective enabler for collaborative coding, has been attested for its success in countless projects around the world. Hence, applying the Git philosophy to general data collaboration beyond coding is motivating. We call it Git for data. However, the original Git design handles data at the file granule, which is considered too coarse-grained for many database applications. We argue that Git for data should be co-designed with database systems. To this end, we developed ForkBase to make Git for data practical. ForkBase is a distributed, immutable storage system designed for data version management and data collaborative operation. In this demonstration, we show how ForkBase can greatly facilitate collaborative data management and how its novel data deduplication technique can improve storage efficiency for archiving massive data versions.