RDFox, the first market ready high-performance in-memory knowledge graph and semantic reasoner. Designed at the University of Oxford for performance and scalability.
Database to overcome flexibility and performance limitations

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

RDFox was designed around high-speeds at the University of Oxford

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

The Radcliffe Camera, a landmark of Oxford University, the birthplace of RDFox

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

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

Data integration for enriching your business

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

RDFox is an in-memory scalable solution for all devices and servers

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

Try it for yourself:
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Working with RDFox

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Reasoning

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

RDF triples illustrated

Triples

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

RDFox was designed around high-speeds at the University of Oxford

Efficiency

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

Explainability

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

Who is the best Formula One driver of all time?

With so many variables in play, this is hardly an easy question to answer. But thankfully, complex questions are our specialty.

Go to f1.rdfox.tech to find the answer.

Read the White Papers

Features

Capabilities
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

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

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

Reasonable Vehicles
Rule the Road

To get a driving license, humans learn the rules;
so should autonomous vehicles

RDFox for Autonomous Vehicles

White Paper 2020

High performance knowledge graph and semantic reasoning engine.

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