Overcome the flexibility and performance limitations of alternative databases, with an in-memory RDF-triplestore

Improve workplace efficiency with semantic technology, unmatched in power, speed and reasoning capabilities ​​

Employ novel designs and concepts, developed at the University of Oxford, and validated in over a decade of peer reviewed research

Optimise speed and parallel reasoning, whilst ensuring correct rule materialisations and query results

Maximise the potential of your business by integrating, enriching, verifying and querying data from various data sources​​

Operate at scale and on the fly, on both production grade servers and memory constrained devices

See the use cases...

Working with RDFox


Rules are modelled with the industry standard Datalog language, and can operate incrementally.


RDFox ingests data in the open standard RDF-triple format which can easily be converted to and from SQL or CSV sources.


Improve enterprise performance with the fastest loading linked data triplestore and by materalising data ahead of query time.​


Access a deeper layer of knowledge with RDFox’s novel explainability feature.

Read the White Papers


Compatible with a wide range of data sources
Highly optimised data structure, with lock-free parallel inserts
OWL 2RL Ontologies
Extensions to Datalog e.g. AGGREGATE, FILTER, Negation as a Failure
Existential rules for restructuring data
SPARQL query answering

Scalable and robust performance
Datalog and SWRL rules
Main memory multi-core architecture
Highly optimised data loading and
query answering
Rules and triples amendments
on the fly
Parallel and incremental reasoning

Supported on windows, Mac OS and Linux
SSL Security
Access controls
Tested on Kubernetes
User console
Ready to deploy as a docker image

High performance knowledge graph and semantic reasoning engine.