As of today, users have the option to run RDFox in Docker using official images from Oxford Semantic Technologies. In this article I will describe how to deploy these images to a multi-zone Kubernetes cluster to achieve a high-availability, read-only configuration.

RDFox is a high-performance knowledge graph and semantic reasoning engine. It is an in-memory solution, which allows flexible incremental addition and retraction of data, and incremental reasoning. It is mathematically validated at the University of Oxford. Since v3, RDFox also offers the ability to incrementally save updates to persistent storage for easier restarts.

Previously, customers wishing to run RDFox…


Photo by Jessica Lee on Unsplash

RDFox v3.1.0 was released on the 7th July 2020. Along with the addition of SWRL support and a slew of small improvements and fixes, the new version introduces an exciting new feature to improve support for applications that require reasoning under the closed-world assumption: Datalog Constraints.

Update: the examples in this article were modified to be compatible with RDFox v4.1.0 (release notes here).

Datalog Constraints leverage RDFox’s unique incremental reasoning capabilities to bring the expressiveness of RDFox’s rule language to the problem of constraining data store content. …

Nick Form

Software Engineer at Oxford Semantic Technologies

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