RDFox is the first market-ready knowledge graph designed from the ground up with reasoning in mind. RDFox is a main-memory data store that allows users to efficiently manage graph-structured data represented according to the RDF data model and query that data using the SPARQL 1.1 query language.
RDFox also enables intelligent information processing by providing means for representing and reasoning with domain knowledge in the form of rules and ontologies. Rules in RDFox can be represented using an extension of the Datalog language, whereas ontologies can be represented in the standard OWL 2 language and in the Semantic Web Rule Language, SWRL.
Oxford Semantic Technologies' RDFox product is supported on the AWS Marketplace by Data Lens Labs Ltd.
This offering can only be used for non-production environments. For questions related to full production licenses via a Private Offer, please contact us at https://www.data-lens.com/#contact.
Highlights
Best-in-class query performance via the W3C Semantic Web Standards SPARQL query language.
Reasoning over OWL ontologies and rules.
Incremental materialisation over ontologies and rules.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
You pay by the container hour. This is usage-based pricing with a single dimension. You are billed for the time your RDFox instance runs as a container task, measured in hours. There are no tiers or fixed commitments. Your cost scales directly with how long you keep the instance running. You deploy the instance using an AWS CloudFormation template, which runs RDFox as a task on an ECS cluster. Billing accrues while that container operates. Stopping the instance stops the hourly charges.
Top-of-mind questions for buyers
What counts as one billed container hour for this RDFox instance?
One container hour is one hour that your RDFox instance runs as a task on the ECS cluster. The meter tracks the running time of that container. Partial usage is measured in hours. Charges accrue continuously while the task operates.
Am I charged when the RDFox container is stopped or not running?
Software charges apply only while the container task runs. Stopping the task stops the hourly software charges. Data stored on the attached EBS volume may still incur separate AWS storage fees, but the RDFox software meters running time only.
Is this pay-as-you-go, or do I commit to a fixed term upfront?
This is pay-as-you-go. You meter actual container hours with no upfront commitment or fixed term. You deploy the instance using an AWS CloudFormation template, then pay for the hours it runs. There are no tiers to select. This suits variable or intermittent workloads.
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Version release notes
Fixed a security vulnerability that exposed PostgreSQL connection strings in error messages (RD-2612). See the security advisory RD-2612 - 7.0 (High) for more details.
UK business hours support please allow 24 hours https://www.data-lens.com/#contact.
We do not currently support refunds, but you can cancel at any time.
AWS infrastructure support
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Supports SPARQL 1.1 query language for querying graph-structured data according to W3C Semantic Web Standards with best-in-class performance.
Ontology and Rule Reasoning
Enables reasoning over OWL 2 ontologies and Semantic Web Rule Language (SWRL) for intelligent information processing and domain knowledge representation.
Datalog-based Rule Representation
Supports rule representation using an extension of the Datalog language for expressing domain knowledge and logical constraints.
Incremental Materialization
Provides incremental materialization capabilities over ontologies and rules to efficiently compute and update derived facts.
In-Memory RDF Data Store
Main-memory data store designed to efficiently manage and query graph-structured data represented according to the RDF data model.
Graph Database Compatibility
Supports Amazon Neptune and any SPARQL 1.1 compliant graph database
RDF Data Management
Provides UI for data loading, ontology library, SPARQL query interface, query catalog, and data quality dashboard for RDF data and ontology management
Web Component Framework
Includes pre-built Web components for search, exploration, authoring, editing, visualization, and graph data interaction that can be configured and combined for rapid development
Knowledge Graph Lifecycle Support
Supports authoring, curating, editing, exploring, integrating, searching, and visualizing of Knowledge Graphs
FAIR Data Compliance
Implements FAIR Data principles for Knowledge Graph management and enterprise data governance
Multi-Model Database Management
Supports both relational tables and RDF graphs within a single integrated database management system
Query Language Support
Provides support for SQL, SPARQL, GraphQL, ODBC/JDBC, HTTP, and MCP protocols for data access and integration
Data Virtualization and Replication
Includes advanced data virtualization, replication, and integration capabilities for managing distributed data sources
Access Control
Implements fine-grained, attribute-based access controls for secure data management
LLM Integration Infrastructure
Delivers infrastructure for developing and deploying Large Language Model-based AI Agents and Assistants with loose coupling to data spaces including databases, knowledge graphs, filesystems, and APIs
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