Graph Database

Graph databases are data structures that represent information as nodes and edges, enabling efficient querying and analysis of relational data. Current research focuses on integrating graph databases with large language models (LLMs) to improve natural language querying (NL2GQL) and leverage LLMs for graph-based tasks, often surpassing traditional graph neural network (GNN) approaches. This integration enhances data management, particularly for complex logical queries and incomplete data, leading to improved performance in diverse applications like finance and medicine. The resulting advancements are significant for fields requiring efficient management and analysis of interconnected data.