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

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Jacopo Urbani, Ceriel J. H. Jacobs, Markus Krötzsch

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



Abstract. 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.

Published at ISWC2016 Posters and Demos (Workshop paper)

Download PDF (last update: 11 Nov 2016)

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Remarks

This is a short demo of the Datalog reasoner VLog. The underlying research is described in detail in the AAAI 2016 publication Column-Oriented Datalog Materialization for Large Knowledge Graphs, which should be cited instead.

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