RDFox

Overview

RDFox is an in-memory store for RDF graphs, pairing SPARQL queries with rule-based reasoning. It is best suited to teams building knowledge-graph applications where new data must quickly update inferred relationships. Its strongest case is fast incremental reasoning; its commercial-license cost requires a direct conversation with Oxford Semantic Technologies.

Key features

RDFox brings graph storage and SPARQL 1.1 querying together with rules and ontological axioms expressed through Datalog, OWL 2 and SWRL. It also supports OWL 2 RL and SHACL. This makes it more than a place to store and retrieve triples: applications can derive consequences from graph data and work with supported knowledge-graph standards.

Incremental reasoning is the clearest differentiator. RDFox updates rule consequences as data changes and can process 2–3 million new-fact inferences per second. That capability suits workloads where incoming facts need to affect the knowledge model promptly; teams should still assess the stated rate against their own rules and data.

Java applications can use a native API, while a RESTful API supports operating RDFox as a standalone server. Import and export support includes CSV, JSON, N-Triples, Turtle, N-Quads, TriG, Datalog and OWL 2 Functional-Style Syntax. Replication across multiple servers helps keep knowledge and data changes available during an outage.

Deployment can be on cloud, on-premises, on-device or at the edge, and RDFox runs on Linux, macOS and Windows. Docker images are designed to run without superuser capabilities. Security capabilities include encryption at rest, mutual TLS client-certificate authentication for endpoint and remote-shell requests, and OpenID Connect single sign-on, including integration with external identity systems such as Microsoft Entra. Encrypted data import and export is supported through Java APIs.

A DataLens partnership made RDFox available through AWS Marketplace with pay-as-you-go deployment and connectors for SQL, CSV, XML, JSON, REST and unstructured data. Oxford Semantic Technologies aims to respond to contact messages within two working days and provides a community Slack channel. The company, founded in 2017 as an Oxford University spin-out, was acquired by Samsung Electronics in 2024.

Pricing

The free license gives teams a month to evaluate RDFox, but it does not permit commercial use. Commercial deployment requires a license key and custom pricing, so it is a poor fit for buyers who need a known per-seat or fixed subscription cost before choosing a system.

Platforms

RDFox supports Linux, macOS and Windows, with API, web and self-hosted options. Its cloud, on-premises, on-device and edge deployment choices accommodate different infrastructure needs, while the Java and REST APIs offer distinct integration paths.

Who it's for

RDFox is a strong candidate for engineering teams building RDF-based applications that need SPARQL querying, standards-based reasoning and frequent updates to inferred knowledge. Its deployment range, replication and integration options are relevant when a graph service must fit existing infrastructure or maintain availability across servers. It is less suitable for an individual or organization seeking unrestricted free commercial use, or for a buyer who must compare transparent license prices before engaging a vendor.

Pros and cons

Pros

• Fast incremental reasoning: Updates to data can flow through rule consequences in real time, with a stated capacity of 2–3 million new-fact inferences per second.
• Broad standards and format support: SPARQL 1.1, Datalog, SWRL, OWL 2 RL and SHACL support varied graph and reasoning workflows.
• Flexible deployment and integration: Linux, macOS and Windows support, multiple deployment settings, and native Java and RESTful APIs give teams several ways to fit RDFox into an application stack.
• Availability and security options: Multi-server replication, encryption at rest, mutual TLS and OpenID Connect address service continuity and access controls.

Cons

• Commercial pricing is not fixed upfront: Buyers must request a quote and obtain a license key, making early cost comparisons harder.
• The free license is only for evaluation: Its 30-day term and non-commercial restriction rule it out as a permanent free option for production use.

Alternatives

Knowledge Graph Software and RDF Databases provide broader category comparisons.

• AllegroGraph is worth considering if a free plan capped at 5 million triples or an enterprise option with customized pricing better matches the project.
• GraphDB is another free-plan option; its free edition is single-core, with a valid license required from GraphDB 11.0.0, while enterprise pricing is custom.
• Protégé is a free, open-source choice for OWL 2 ontology work on desktop or the web.
• RDF Studio offers a free semantic data workspace with no stated price or usage limits.
• TypeDB may suit teams seeking a managed dedicated database server; its Explore plan includes 10 GB storage, 8 GB RAM and 2 vCPUs.
• Eclipse RDF4J is a free, open-source Java framework; its latest release requires Java 25 or newer.
• QLever is a free option released under the Apache 2.0 license.
• Stardog is another option to compare for graph database needs.

Verdict

Choose RDFox if your team needs RDF storage with fast, continuously updated reasoning, and values multiple deployment and integration routes. Its technical strengths are clearest for applications where fresh facts must quickly change inferred knowledge. Look elsewhere if commercial cost transparency or a free production license is essential: evaluation is limited to 30 days and commercial use requires a custom quote and license key.