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A Survey Of Persistent Graph Databases

Liu, Yufan
http://rave.ohiolink.edu/etdc/view?acc_num=kent1395166105

Abstract Details

2014, MS, Kent State University, College of Arts and Sciences / Department of Computer Science.
Graph database has attracted increasing attention from both of the database and data mining/machine learning communities. Enormous kinds of data with complex and dynamic relationships can be efficiently expressed by graph structure. Certain techniques such as scoring, shortest path and clustering can provide information and services by leveraging those data. They are widely used in areas like Web graph mining (Google), social network analysis (Facebook), User/Product recommendation (Netflix/Amazon), chemical and biological analysis, etc. Graph databases provide a fast and efficient way to store, access and analysis those kinds of data than any other database system. This thesis will go over the graph data and its representations, then categorize some of the most commonly used graph databases by their storage behavior. Then we will introduce some of the state-of-the-art techniques that enpower the graph database internally. After the introduction, we will have the study on how to access the graph database through query languages or APIs, and compare them through different aspects. Another contribution of this work is to compare the performance to process different kinds of data between the persistent graph databases. Not only the performance of batch loading process has been compared, we also have the stress test on single transactional insertion, query, and the in-memory graph algorithm comparison. At last we have some recommendations of using the databases based on the experiment result.
Ruoming Jin (Advisor)
46 p.
Computer Engineering; Computer Science
graph database; graph mining; transactional database; benchmark; graph algorithm; GDB; distribute graph processing framework; NOSQL;

Recommended Citations

Citations

  • Liu, Y. (2014). A Survey Of Persistent Graph Databases [Master's thesis, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1395166105

    APA Style (7th edition)

  • Liu, Yufan. A Survey Of Persistent Graph Databases. 2014. Kent State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1395166105.

    MLA Style (8th edition)

  • Liu, Yufan. "A Survey Of Persistent Graph Databases." Master's thesis, Kent State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1395166105

    Chicago Manual of Style (17th edition)

kent1395166105
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© 2014, some rights reserved.Creative Commons License A Survey Of Persistent Graph Databases by Yufan Liu is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by Kent State University and OhioLINK.