Towards an Integrated Graph Algebra for Graph Pattern Matching with Gremlin

  • Harsh ThakkarEmail author
  • Dharmen Punjani
  • Sören Auer
  • Maria-Esther Vidal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10438)


Graph data management has revealed beneficial characteristics in terms of flexibility and scalability by differently balancing between query expressivity and schema flexibility. This has resulted into an rapid developing new task specific graph systems, query languages and data models, such as property graphs, key-value, wide column, resource description framework (RDF), etc. Present day graph query languages are focused towards flexible graph pattern matching (aka sub-graph matching), where as graph computing frameworks aim towards providing fast parallel (distributed) execution of instructions. The consequence of this rapid growth in the variety of graph based data management systems has resulted in a lack of standardization. Gremlin, a graph traversal language and machine, provides a common platform for supporting any graph computing system (such as an OLTP graph database or OLAP graph processors). We present a formalization of graph pattern matching for Gremlin queries. We also study, discuss and consolidate various existing graph algebra operators into an integrated graph algebra.


Graph pattern matching Graph traversal Graph query algebra 



This work is supported by the EU H2020 WDAqua ITN (GA: 642795).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Harsh Thakkar
    • 1
    Email author
  • Dharmen Punjani
    • 2
  • Sören Auer
    • 1
    • 3
  • Maria-Esther Vidal
    • 1
  1. 1.University of BonnBonnGermany
  2. 2.National and Kapodistrian University of AthensAthensGreece
  3. 3.Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS)Sankt AugustinGermany

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