RDFox

Overview

RDFox is a main-memory store for RDF graph data, queried with SPARQL 1.1 and paired with rules-based reasoning. It suits teams building knowledge-graph applications that need reasoning to keep pace with changing data, especially when deployment flexibility and server integration matter.

Its real-time incremental reasoning and broad deployment options are compelling; the main drawback is that commercial licensing requires a custom quote, while the free evaluation license is restricted to non-commercial evaluation.

Key features

RDFox brings RDF storage and querying together with reasoning based on Datalog rules and ontological axioms, including OWL 2 and SWRL. It also supports SHACL. That combination is useful when an application must derive consequences from graph data rather than simply store and retrieve triples.

Its standout capability is incremental reasoning: RDFox updates rule consequences as data changes and can process 2–3 million new-fact inferences per second. That makes it a strong fit for workloads where graph updates should quickly flow through the knowledge model, though the published throughput figure is not a substitute for checking performance against a particular workload.

For application integration, a native API serves Java applications, while a RESTful API lets teams operate RDFox as a standalone server. It imports and exports formats including CSV, JSON, N-Triples, Turtle, TriG and OWL 2 Functional-Style Syntax; its supported import formats also include N-Quads and Datalog. Replication across multiple servers can keep knowledge and data changes available during an outage, a meaningful option for services where interruption matters.

Security capabilities include encryption at rest and mutual-TLS client-certificate authentication for endpoint and remote-shell requests. Version 7.1 adds OpenID Connect single sign-on, including external identity systems such as Microsoft Entra, and encrypted data import and export through Java APIs. Official Docker images are designed to run without superuser capabilities.

RDFox is deployed on cloud, on-premises, on-device and at the edge, and runs on Linux, macOS and Windows. An AWS Marketplace route offers pay-as-you-go deployment through a DataLens partnership, with connectors for SQL, CSV, XML, JSON, REST and unstructured data.

Pricing

The RDFox free evaluation license costs nothing for a 30-day trial. It is limited to evaluation and non-commercial use, so it is not a continuing free tier for production or paid projects.

The RDFox commercial license has custom pricing and requires a license key; buyers must contact Oxford Semantic Technologies. Teams that need a commercial deployment should factor in that quote-based process before choosing RDFox. No commercial seat or usage cap is stated.

Platforms

RDFox supports Linux, macOS and Windows, with API, web and self-hosted deployment options. Its cloud, on-premises, on-device and edge deployment choices suit organizations that need control over where graph data runs rather than a single hosting model.

Who it's for

RDFox is best suited to engineering and data teams building RDF knowledge graphs that need SPARQL 1.1, rule-based inference and rapid updates to derived facts. Java and REST APIs, data-format support and replication make it relevant to teams integrating graph capabilities into applications or services. It is a less natural choice for casual or commercial users seeking an ongoing free plan, since the free license is temporary and non-commercial and commercial pricing is custom.

Pros and cons

• Pro: Incremental reasoning updates consequences as data changes, with a stated capacity of 2–3 million new-fact inferences per second.
• Pro: Java and REST APIs, broad data-format support and multiple deployment settings offer practical integration flexibility.
• Pro: Multi-server replication and security features such as mutual TLS and OpenID Connect support operational and access-control needs.
• Con: The free evaluation lasts 30 days and excludes commercial use, so it cannot serve as a long-term free production option.
• Con: Commercial licensing requires contacting the vendor for custom pricing, which gives buyers no published price to compare upfront.

Alternatives

For a broader shortlist, browse Knowledge Graph Software and RDF Databases.

• AllegroGraph is worth considering if a free option with a stated allowance is important: its free plan covers up to 5 million triples, while enterprise pricing is customized.
• Eclipse RDF4J is a free, open-source Java framework for teams who prefer a framework rather than RDFox's commercial licensing model; its latest release requires Java 25 or newer.
• GraphDB offers a free single-core license, making it an alternative for workloads that can fit that limit; its Enterprise plan uses custom pricing.
• Protégé is a free, open-source option with OWL 2 support for readers focused on ontology work.
• RDF Studio is a free semantic data workspace to consider as another no-cost option.
• Stardog may suit a smaller project that fits its free plan's 1 million stored edges and three-database limit; that plan includes a renewable one-year license and excludes high availability.
• TypeDB is an alternative for readers seeking a fully managed dedicated database server, with its Explore plan offering 10 GB storage, 8 GB RAM and 2 vCPUs.
• Apache Jena Fuseki is a free, self-hosted server option for teams who prefer software under the Apache License 2.0.

Verdict

Choose RDFox when your knowledge-graph application needs SPARQL querying plus fast, incremental reasoning, and you value the choice of deployment and integration paths. Its clearest advantage is keeping derived facts current as data changes; its clearest reason to look elsewhere is the lack of a continuing commercial-use free plan and the need to obtain a custom commercial quote.