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Olafs Vandans

dblp:263/1945 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 87% Distributed systems · 13%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems › data reduction
data deduplication
0.412020
ForkBase: Immutable, Tamper-evident Storage Substrate for Branchable Applications · ICDE 2020
Storage systems › storage management
versioned storage
0.412020
ForkBase: Immutable, Tamper-evident Storage Substrate for Branchable Applications · ICDE 2020

Methods — techniques the papers use, named apart from their topics

hash-based deduplication · 0.4content-addressed storage · 0.4
YearPublicationVenuePosition
2020 ForkBase: Immutable, Tamper-evident Storage Substrate for Branchable Applications
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.
Qian Lin 0002, Kaiyuan Yang 0003, Tien Tuan Anh Dinh, Qingchao Cai, Gang Chen 0001, Beng Chin Ooi, Pingcheng Ruan, Sheng Wang 0011, Zhongle Xie, Meihui Zhang 0001, Olafs Vandans
ICDE11