Current Status and Application Analysis of Graph Database Technology

Liu, Yuning; Qu, Shiqi; Fan, Bingbing

doi:10.1109/mlbdbi54094.2021.00144

Cited by 2 publications

(3 citation statements)

References 21 publications

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“…Multimodal transport networks were constructed using a Neo4j graph database, currently the most popular native graph database available (Liu et al, 2021; Maduako et al, 2018). The location and properties of nodes and relationships representing node‐to‐node connections were derived from the prebuilt dataset for transport, such as road networks.…”

Section: Methodsmentioning

confidence: 99%

“…Intuitive data models enable the effective storage of data describing complex real-world transportation systems; whereas the flexible data schema allows for the model to be readily extended to accommodate updates of transport networks and timetables. Moreover, graph databases can search and load only relevant data according to its built-in index structure (Liu et al, 2021); thus, the query performance is excellent for large datasets (De Virgilio et al, 2014). Furthermore, due to its strong scalability, graph traverse can be executed across all data sizes with consistent performance (Angles & Gutierrez, 2018).…”

mentioning

confidence: 99%

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Framework for constructing multimodal transport networks and routing using a graph database: A case study in London

Park

Cheng

2023

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Most prior multimodal transport networks have been organized as relational databases with multilayer structures to support transport management and routing; however, database expandability and update efficiency in new networks and timetables are low due to the strict database schemas. This study aimed to develop multimodal transport networks using a graph database that can accommodate efficient updates and extensions, high relation‐based query performance, and flexible integration in multimodal routing. As a case study, a database was constructed for London transport networks, and routing tests were performed under various conditions. The constructed multimodal graph database showed stable performance in processing iterative queries, and efficient multi‐stop routing was particularly enhanced. By applying the proposed framework, databases for multimodal routing can be readily constructed for other regions, while enabling responses to diversified routings, such as personalized routing through integration with various unstructured information, due to the flexible schema of the graph database.

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Section: Methodsmentioning

confidence: 99%

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confidence: 99%

Framework for constructing multimodal transport networks and routing using a graph database: A case study in London

Park

Cheng

2023

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“…Equipment and connection relationships are stored in separate tables, namely the equipment and relationship tables. In the traditional relational model, equipment and relationships can be equivalently represented as nodes and edges in a graph model [21].…”

Section: Power Transfer Scheme Based On Graph Databasementioning

confidence: 99%

Research on a Unified Data Model for Power Grids and Communication Networks Based on Graph Databases

Li,

Yang,

Liu

et al. 2024

Electronics

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With the continuous development of the power grid, its structure is becoming increasingly complex. The occurrence of faults in transmission lines may lead to cascading failures in the power grid, ultimately resulting in widespread power outages. The transmission of equipment information and the sending of fault reports in the power grid rely on the power communication network. This network is crucial for ensuring the safe, stable, and economical operation of the power grid. As the number of devices in the power grid increases and sensor technology becomes more widespread, the volume of data generated by both the power grid and the power communication network has increased sharply. However, relational databases have limited scalability and struggle to meet the growing volume of data and user demands. This paper proposes a graph mapping method based on the power grid and communication network, utilizing data from both networks to construct a unified data plane in a graph database. Taking power transfer operations as an example, a unified standard data model and monitoring indicator system are established for both networks, enabling faster response and power restoration to blackout areas in the event of power grid faults. Simulation results demonstrate that compared to traditional relational databases, graph databases exhibit significantly improved efficiency in handling large-scale, highly connected data, making them more suitable for future power grids.

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Current Status and Application Analysis of Graph Database Technology

Cited by 2 publications

References 21 publications

Framework for constructing multimodal transport networks and routing using a graph database: A case study in London

Framework for constructing multimodal transport networks and routing using a graph database: A case study in London

Research on a Unified Data Model for Power Grids and Communication Networks Based on Graph Databases

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