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In-Memory Object Graph Stores

Authors Aditya Thimmaiah , Zijian Yi , Joseph Kenis , Christopher J Rossbach , Milos Gligoric

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Subject Classification

ACM Subject Classification
  • Software and its engineering
Keywords
  • Object stores
  • Graph stores
  • Cypher

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Abstract

We present a design and implementation of an in-memory object graph store, dubbed εStore. Our key innovation is a storage model - epsilon store - that equates an object on the heap to a node in a graph store. Thus any object on the heap (without changes) can be a part of one, or multiple, graph stores, and vice versa, any node in a graph store can be accessed like any other object on the heap. Specifically, each node in a graph is an object (i.e., instance of a class), and its properties and its edges are the primitive and reference fields declared in its class, respectively. Necessary classes, which are instantiated to represent nodes, are created dynamically by εStore. εStore uses a subset of the Cypher query language to query the graph store. By design, the result of any query is a table (ResultSet) of references to objects on the heap, which users can manipulate the same way as any other object on the heap in their programs. Moreover, a developer can include (transitively) an arbitrary object to become a part of a graph store. Finally, εStore introduces compile-time rewriting of Cypher queries into imperative code to improve the runtime performance. εStore can be used for a number of tasks including implementing methods for complex in-memory structures, writing complex assertions, or a stripped down version of a graph database that can conveniently be used during testing. We implement εStore in Java and show its application using the aforementioned tasks.

Cite As Get BibTex

Aditya Thimmaiah, Zijian Yi, Joseph Kenis, Christopher J Rossbach, and Milos Gligoric. In-Memory Object Graph Stores. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 30:1-30:30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.ECOOP.2025.30

Author Details

Aditya Thimmaiah
  • The University of Texas at Austin, TX, USA
Zijian Yi
  • The University of Texas at Austin, TX, USA
Joseph Kenis
  • The University of Texas at Austin, TX, USA
Christopher J Rossbach
  • The University of Texas at Austin, TX, USA
Milos Gligoric
  • The University of Texas at Austin, TX, USA

Funding

This work is partially supported by the US National Science Foundation under Grant Nos. CCF-2107291, CCF-2217696, CCF-2313027, and CCF-2403036.

Acknowledgements

We thank Michael Y. Levin, Zhiqiang Zang, Yu Liu, Nader Al Awar, Jiyang Zhang, Linghan Zhong, Cheng Ding, Ivan Grigorik, Tong-Nong Lin and the anonymous reviewers for their feedback on this work.

Supplementary Materials

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