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Evaluation of Contemporary Graph Databases for Efficient Persistence of Large-Scale Models

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Evaluation of Contemporary Graph Databases for Efficient Persistence of Large-Scale Models. / Barmpis, Konstantinos; Kolovos, Dimitris.

In: Journal of Object Technology, Vol. 13, No. 3, 07.2014, p. 3:1-26.

Research output: Contribution to journalArticle

Harvard

Barmpis, K & Kolovos, D 2014, 'Evaluation of Contemporary Graph Databases for Efficient Persistence of Large-Scale Models', Journal of Object Technology, vol. 13, no. 3, pp. 3:1-26. https://doi.org/doi:10.5381/jot.2014.13.3.a3

APA

Barmpis, K., & Kolovos, D. (2014). Evaluation of Contemporary Graph Databases for Efficient Persistence of Large-Scale Models. Journal of Object Technology, 13(3), 3:1-26. https://doi.org/doi:10.5381/jot.2014.13.3.a3

Vancouver

Barmpis K, Kolovos D. Evaluation of Contemporary Graph Databases for Efficient Persistence of Large-Scale Models. Journal of Object Technology. 2014 Jul;13(3):3:1-26. https://doi.org/doi:10.5381/jot.2014.13.3.a3

Author

Barmpis, Konstantinos ; Kolovos, Dimitris. / Evaluation of Contemporary Graph Databases for Efficient Persistence of Large-Scale Models. In: Journal of Object Technology. 2014 ; Vol. 13, No. 3. pp. 3:1-26.

Bibtex - Download

@article{abe71632b77d4059a7658d467e6538bd,
title = "Evaluation of Contemporary Graph Databases for Efficient Persistence of Large-Scale Models",
abstract = "Scalability in Model-Driven Engineering (MDE) is often a bottleneck for industrial applications. Industrial scale models need to be persisted in a way that allows for their seamless and efficient manipulation, often by multiple stakeholders simultaneously. This paper compares the conventional and commonly used persistence mechanisms in MDE with novel approaches such as the use of graph-based NoSQL databases; Prototype integrations of Neo4J and OrientDB with EMF are used to compare with relational database, XMI and document-based NoSQL database persistence mechanisms. It also compares and benchmarks two approaches for querying models persisted in graph databases to measure and compare their relative performance in terms of memory usage and execution time.",
keywords = "Scalability, Persistence, Model-driven engineering",
author = "Konstantinos Barmpis and Dimitris Kolovos",
year = "2014",
month = "7",
doi = "doi:10.5381/jot.2014.13.3.a3",
language = "English",
volume = "13",
pages = "3:1--26",
journal = "Journal of Object Technology",
issn = "1660-1769",
publisher = "Journal of Object Technology",
number = "3",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Evaluation of Contemporary Graph Databases for Efficient Persistence of Large-Scale Models

AU - Barmpis, Konstantinos

AU - Kolovos, Dimitris

PY - 2014/7

Y1 - 2014/7

N2 - Scalability in Model-Driven Engineering (MDE) is often a bottleneck for industrial applications. Industrial scale models need to be persisted in a way that allows for their seamless and efficient manipulation, often by multiple stakeholders simultaneously. This paper compares the conventional and commonly used persistence mechanisms in MDE with novel approaches such as the use of graph-based NoSQL databases; Prototype integrations of Neo4J and OrientDB with EMF are used to compare with relational database, XMI and document-based NoSQL database persistence mechanisms. It also compares and benchmarks two approaches for querying models persisted in graph databases to measure and compare their relative performance in terms of memory usage and execution time.

AB - Scalability in Model-Driven Engineering (MDE) is often a bottleneck for industrial applications. Industrial scale models need to be persisted in a way that allows for their seamless and efficient manipulation, often by multiple stakeholders simultaneously. This paper compares the conventional and commonly used persistence mechanisms in MDE with novel approaches such as the use of graph-based NoSQL databases; Prototype integrations of Neo4J and OrientDB with EMF are used to compare with relational database, XMI and document-based NoSQL database persistence mechanisms. It also compares and benchmarks two approaches for querying models persisted in graph databases to measure and compare their relative performance in terms of memory usage and execution time.

KW - Scalability

KW - Persistence

KW - Model-driven engineering

U2 - doi:10.5381/jot.2014.13.3.a3

DO - doi:10.5381/jot.2014.13.3.a3

M3 - Article

VL - 13

SP - 3:1-26

JO - Journal of Object Technology

JF - Journal of Object Technology

SN - 1660-1769

IS - 3

ER -