Scalable time-versioning support for property graph databases

Warut D. Vijitbenjaronk, Jinho Lee, Toyotaro Suzumura, Gabriel Tanase

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


When graphs change over time, it is important to make the changes trackable for many graph-based applications. We propose an implementation of OLTP-oriented graph database that supports time-versioning. There has been a few snapshot-based approaches for supporting time-versions, but they usually require the full-restoration of the graph, and lack the resolution of the time space. Using a B-tree as the datastructure for the backend storage, our database allow fast and scalable support for restoring the arbitrary part of the graph, without slowing down the normal accesses to the current graph. Experimental results show that our scheme is much efficient than the straightforward solutions, in terms of space and performance.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
EditorsJian-Yun Nie, Zoran Obradovic, Toyotaro Suzumura, Rumi Ghosh, Raghunath Nambiar, Chonggang Wang, Hui Zang, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Xiaohua Hu, Jeremy Kepner, Alfredo Cuzzocrea, Jian Tang, Masashi Toyoda
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages10
ISBN (Electronic)9781538627143
Publication statusPublished - 2017 Jul 1
Event5th IEEE International Conference on Big Data, Big Data 2017 - Boston, United States
Duration: 2017 Dec 112017 Dec 14

Publication series

NameProceedings - 2017 IEEE International Conference on Big Data, Big Data 2017


Conference5th IEEE International Conference on Big Data, Big Data 2017
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Control and Optimization


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