Encyclopedia of Big Data Technologies

2019 Edition
| Editors: Sherif Sakr, Albert Y. Zomaya

Graph Data Management Systems

  • Marcus ParadiesEmail author
  • Stefan PlantikowEmail author
  • Oskar van RestEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-3-319-77525-8_82


The abundance and diversity of massive-scale, graph-structured data and the ever-growing interest of large enterprise companies to analyze them are the key drivers of the recent advances in graph data management research. Further, graph data management has witnessed a steady increase in applications from various industry domains, such as social media, logistics and transportation, gas and oil utility networks, finance, public security, and the pharmaceutical industry.

The widespread adoption of graph technology and the diversity in requirements for the aforementioned application domains are the key drivers for the development of a variety of graph data management systems (gdmss). These gdmss are typically tailored to a specific graph workload, which is distinctive to the application domain and drives the design of the core system components, such as the primary/secondary storage, the query execution engine, and the user interface(s).

From a data model perspective,...

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.SAP SEWalldorfGermany
  2. 2.SAP SEBerlinGermany
  3. 3.Neo4jBerlinGermany
  4. 4.OracleCAUSA