.png){kind=icon}
.png){kind=icon}
Return
GETL: An Extract-Transform-Load Framework Across Graph Models in Graph Warehouse
.png){kind=icon}
PRE
AI
DOI：10.1109/TKDE.2026.3655790.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Various graph models have emerged to meet diverse application needs, each with unique characteristics and specialties. Managing and analyzing graph data inevitably requires interactions across different models to serve upstream business requirements. Therefore, an Extract-Transform-Load (ETL) tool designed to bridge different graph models is desired. In this paper, we propose $\mathsf {GETL}$, a generalized graph ETL framework capable of automatically identifying graph model schemas and performing seamless data conversion among RDF, RDF-star, labeled property graph, and the relational model. This is attributed to $\mathsf {GETL}$’s unified graph representation model, constructed as nested $< $label, entity$> $ pairs, offering powerful capabilities in graph representation and model compatibility. Additionally, we develop a unified programming interface to support complex graph transformation tasks. It is built upon the Gremlin syntax and provides strong expressive capabilities. Finally, our evaluation demonstrates that $\mathsf {GETL}$ outperforms state-of-the-art solutions in terms of model conversion efficiency and data manipulation language (DML) intelligibility.
Keywords:
Graph ETL framework
unified graph representation
programming interface
Journal
IF:
10.4
Papers:
6.8K
Citations:
3.2W