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Journal of Advanced Engineering and Computation, 2017 Comparing graph databases with traditional,e.g., relational databases, some important database features are often missing there. Particularly, a graph database schema including integrity constraints is mostly not explicitly defined, also a conceptual ...
Jaroslav Pokorny
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Functional querying in graph databases [PDF]
Vietnam Journal of Computer Science, 2017 The paper is focused on a functional querying in graph databases. We consider labelled property graph model and mention also the graph model behind XML databases. An attention is devoted to functional modelling of graph databases both at a conceptual and
Jaroslav Pokorný
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Mapping RDF Databases to Property Graph Databases [PDF]
IEEE Access, 2020 RDF triplestores and property graph databases are two approaches for data management which are based on modeling, storing and querying graph-like data. In spite of such common principle, they present special features that complicate the task of database ...
Renzo Angles +2 more
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Storage and Query of Drug Knowledge Graphs Using Distributed Graph Databases: A Case Study [PDF]
BioengineeringBackground: Distributed graph databases are a promising method for storing and conducting complex pathway queries on large-scale drug knowledge graphs to support drug research. However, there is a research gap in evaluating drug knowledge graphs’ storage
Xingjian Han, Yu Tian
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Graph databases in systems biology: a systematic review [PDF]
Briefings in BioinformaticsGraph databases are becoming increasingly popular across scientific disciplines, being highly suitable for storing and connecting complex heterogeneous data.
Alexander Mazein +2 more
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EPJ Web of Conferences, 2020 Data in High Energy Physics (HEP) usually consist of complext complex data structures stored in relational databases and files with internal schema.
Hřivnáč Julius
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Experimental Evaluation of Graph Databases: JanusGraph, Nebula Graph, Neo4j, and TigerGraph
Applied Sciences, 2023 NoSQL databases were created with the primary goal of addressing the shortcomings in the efficiency of relational databases, and can be of four types: document, column, key-value, and graph databases.
Jéssica Monteiro +2 more
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Analysing River Systems with Time Series Data Using Path Queries in Graph Databases
ISPRS International Journal of Geo-Information, 2023 Transportation networks are used in many application areas, like traffic control or river monitoring. For this purpose, sensors are placed in strategic points in the network and they send their data to a central location for storage, viewing and analysis.
Erik Bollen +4 more
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biochem4j: Integrated and extensible biochemical knowledge through graph databases. [PDF]
PLoS ONE, 2017 Biologists and biochemists have at their disposal a number of excellent, publicly available data resources such as UniProt, KEGG, and NCBI Taxonomy, which catalogue biological entities. Despite the usefulness of these resources, they remain fundamentally
Neil Swainston +13 more
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Optimizing large-scale graph database ingestion through edge value ranking: a proposed framework [PDF]
Frontiers in Big DataThis paper proposes a preprocessing framework for optimizing large-scale graph database ingestion through intelligent edge filtering based on value ranking. We combine adapted PageRank algorithms with business-specific metrics and edge type importance to
Phanindra Reddy Madduru, Bijo Thomas
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