VLog: A Column-Oriented Datalog System for Large Knowledge Graphs

Jacopo UrbaniJacopo Urbani, Ceriel JacobsCeriel Jacobs, Markus KrötzschMarkus Krötzsch

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Jacopo Urbani, Ceriel Jacobs, Markus Krötzsch
VLog: A Column-Oriented Datalog System for Large Knowledge Graphs
In Takahiro Kawamura, Heiko Paulheim, eds., Proceedings of the 15th International Semantic Web Conf. (ISWC'16), Posters and Demos, volume 1690 of CEUR Workshop Proceedings, 2016. CEUR-WS.org

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KurzfassungAbstract
We present VLog, a new system for answering arbitrary Datalog queries on top of a wide range of databases, including both relational and RDF databases. VLog is designed to perform efficiently intensive rule-based computation on large Knowledge Graphs (KGs). It adapts column-store technologies to attain high efficiency in terms of memory usage and speed, enabling us to process Datalog queries with thousands of rules over databases with hundreds of millions of tuples—in a live demonstration on a laptop. Our demonstration provides in-depth insights into the workings of VLog, and presents important new features such as support for arbitrary relational DBMS.
Bemerkung: Note: This is a demo for the system described in Column-Oriented Datalog Materialization for Large Knowledge Graphs. Please cite the conference version instead.

We also provide a screencast for the demo.
Projekt:Project: DIAMOND, HAEC B08
Forschungsgruppe:Research Group: Wissensbasierte SystemeKnowledge-Based Systems

@inproceedings{UJK2016,
  author    = {Jacopo Urbani and Ceriel Jacobs and Markus Kr{\"{o}}tzsch},
  title     = {{VLog}: A Column-Oriented {Datalog} System for Large Knowledge Graphs},
  editor    = {Takahiro Kawamura and Heiko Paulheim},
  booktitle = {Proceedings of the 15th International Semantic Web Conf.
               (ISWC'16), Posters and Demos},
  series    = {CEUR Workshop Proceedings},
  volume    = {1690},
  publisher = {CEUR-WS.org},
  year      = {2016}
}