GraQL: A Query Language for High-Performance Attributed Graph Databases
Graph databases have gained increasing interest in the last few years due to the emergence of data sources which are not easily analyzable in traditional relational models or for which a graph data model is the natural representation. In order to understand the design and implementation choices for an attributed graph database backend and query language, we have started to design our infrastructure for attributed graph databases. In this paper, we describe the design considerations of our in-memory attributed graph database system with a particular focus on the data definition and query language components.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1339889
- Report Number(s):
- PNNL-SA-116653; 453040300
- Resource Relation:
- Conference: IEEE International Parallel and Distributed Processing Symposium Workshops, May 23-27, 2016, Chicago, Illinois
- Country of Publication:
- United States
- Language:
- English
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