English

Logica-TGD: Transforming Graph Databases Logically

Databases 2025-03-04 v1

Abstract

Graph transformations are a powerful computational model for manipulating complex networks, but handling temporal aspects and scalability remain significant challenges. We present a novel approach to implementing these transformations using Logica, an open-source logic programming language and system that operates on parallel databases like DuckDB and BigQuery. Leveraging the parallelism of these engines, our method enhances performance and accessibility, while also offering a practical way to handle time-varying graphs. We illustrate Logica's graph querying and transformation capabilities with several examples, including the computation of the well-founded solution to the classic "Win-Move" game, a declarative program for pathfinding in a dynamic graph, and the application of Logica to the collection of all current facts of Wikidata for taxonomic relations analysis. We argue that clear declarative syntax, built-in visualization and powerful supported engines make Logica a convenient tool for graph transformations.

Keywords

Cite

@article{arxiv.2503.00568,
  title  = {Logica-TGD: Transforming Graph Databases Logically},
  author = {Evgeny Skvortsov and Yilin Xia and Bertram Ludäscher and Shawn Bowers},
  journal= {arXiv preprint arXiv:2503.00568},
  year   = {2025}
}

Comments

Published in the Proceedings of the Workshops of the EDBT/ICDT 2025 Joint Conference (March 25-28, 2025), Barcelona, Spain

R2 v1 2026-06-28T22:03:11.117Z