arrow
Return

Dataclay: A distributed data store for effective inter-player data sharing

delete2017-09-01
delete22
delete
OA
AI
J
Jonathan Martí *
A
Anna Queralt
D
Daniel Gasull
A
Alex Barceló
J
Juan José Costa
T
Toni Cortés
DOI:10.1016/j.jss.2017.05.080delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
In the Big Data era, both the academic community and industry agree that a crucial point to obtain the maximum benefits from the explosive data growth is integrating information from different sources, and also combining methodologies to analyze and process it. For this reason, sharing data so that third parties can build new applications or services based on it is nowadays a trend. Although most data sharing initiatives are based on public data, the ability to reuse data generated by private companies is starting to gain importance as some of them (such as Google, Twitter, BBC or New York Times) are providing access to part of their data. However, current solutions for sharing data with third parties are not fully convenient to either or both data owners and data consumers. Therefore we present dataClay, a distributed data store designed to share data with external players in a secure and flexible way based on the concepts of identity and encapsulation. We also prove that dataClay is comparable in terms of performance with trendy NoSQL technologies while providing extra functionality, and resolves impedance mismatch issues based on the Object Oriented paradigm for data representation. (C) 2017 Elsevier Inc. All rights reserved.
Keywords:
Data sharing
Distributed databases
NoSQL
Storage systems
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Journal of Systems and Software cover
Journal of Systems and Software
IF:
4.1
Papers:
5.4K
Citations:
8.4K

Organization

U
universitat politecnica de catalunya
Scholars:
1.9W
Papers: 1.6W
Citations: 17