The World of Graph Databases from An Industry Perspective
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Abstract (arXiv)
Rapidly growing social networks and other graph data have created a high demand for graph technologies in the market. A plethora of graph databases, systems, and solutions have emerged, as a result. On the other hand, graph has long been a well studied area in the database research community. Despite the numerous surveys on various graph research topics, there is a lack of survey on graph technologies from an industry perspective. The purpose of this paper is to provide the research community with an industrial perspective on the graph database landscape, so that graph researcher can better understand the industry trend and the challenges that the industry is facing, and work on solutions to help address these problems.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Nov 2022.
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Citing papers per year: 2023: 2; 2024: 3; 2025: 1; 2026: 1.
7 papers.
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- 2025Top Ten Challenges Towards Agentic Neural Graph Databasescited by 13
- 2023Construction of Knowledge Graphs: State and Challengescited by 12
- 2023Knowledge Graphs Queryingcited by 5
- 2024D3-GNN: Dynamic Distributed Dataflow for Streaming Graph Neural Networkscited by 2
- 2024IRSKG: Unified Intrusion Response System Knowledge Graph Ontology for Cyber Defensecited by 1
- 2026From SQL to Knowledge Graphs: An LLM-Driven Multi-Agent Approach with Data Schema Improvementcited by 0
- 2026From SQL to Knowledge Graphs: An LLM-Driven Multi-Agent Approach with Data Schema Improvement17 Jun 2026
- 2025Top Ten Challenges Towards Agentic Neural Graph Databases24 Jan 2025
- 2024IRSKG: Unified Intrusion Response System Knowledge Graph Ontology for Cyber Defense23 Nov 2024
- 2024D3-GNN: Dynamic Distributed Dataflow for Streaming Graph Neural Networks10 Sep 2024
- 2024OpenFGL: A Comprehensive Benchmark for Federated Graph Learning29 Aug 2024
- 2023Knowledge Graphs Querying23 May 2023
- 2023Construction of Knowledge Graphs: State and Challenges22 Feb 2023