research-article

Cytosm: Declarative Property Graph Queries Without Data Migration

Authors:

Benjamin A. Steer,

Alhamza Alnaimi,

Marco A. B. F. G. Lotz,

Felix Cuadrado,

Luis M. Vaquero,

Joan VarvenneAuthors Info & Claims

GRADES'17: Proceedings of the Fifth International Workshop on Graph Data-management Experiences & Systems

Article No.: 4, Pages 1 - 6

https://doi.org/10.1145/3078447.3078451

Published: 19 May 2017 Publication History

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Abstract

The property graph model has recently gained significant popularity, combining great expressiveness with powerful declarative graph query languages. However, in order to take advantage of these features, data must be loaded into a specialised graph database. Additionally, property graphs are often schema-free, complicating efficient query execution. In this paper we present Cytosm, a middleware application which enables the execution of property graph queries, on non-graph databases, without data migration. Cytosm relies on gTop, a schema containing an abstract property graph topology, and its mapping to specific database backends. Cytosm uses gTop to efficiently execute OpenCypher queries, exploiting schema information to optimise the query plan, and mapping query concepts to the relational backend. Our experiments show that Cytosm achieves competitive query execution times on relational backends, when compared to leading graph databases.

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Shen ZHu CZhao Z(2023)Lynx: A Graph Query Framework for Multiple Heterogeneous Data SourcesProceedings of the VLDB Endowment10.14778/3611540.361158716:12(3926-3929)Online publication date: 1-Aug-2023
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GRADES'17: Proceedings of the Fifth International Workshop on Graph Data-management Experiences & Systems

May 2017

87 pages

ISBN:9781450350389

DOI:10.1145/3078447

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 19 May 2017

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SIGMOD/PODS'17: International Conference on Management of Data

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IL, Chicago, USA

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https://dl.acm.org/doi/10.14778/3611540.3611587
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