GraphDB ™

GraphDB ™ is a “semantic repository” using ontologies that allow the repository to automatically reason about the data.

GraphDB is the only graph database RDF triplestore that can perform semantic inferencing at scale allowing users to create new semantic facts from existing facts. GraphDB handles massive loads, queries and inferencing in real time. 

GraphDB works with a flexible and generic physical graph data model allowing for easy interpretation and adoption of new ontologies or metadata on-the-fly.

GraphDB is a semantic repository, packaged as a storage and inference layer (SAIL) for Sesame. Sesame is one of the most popular semantic repositories that supports RDF(S) and all the major syntaxes and query languages related to it.


Data integration and interlinking

This allows very easily merge of information from multiple sources including Linked Open Data or proprietary sources. The ability to recognize entities across multiple sources holds great promise helping to manage your data more effectively and pinpointing connections in your data that may be masked by slightly different entity references. Merging information from various sources produces more accurate results, a clearer picture of how entities are related to one another and the ability to improve the speed with which your organization operates.

GraphDB works with globally unique identifiers, the most popular variant of which are the widely used URLs. All data elements (objects, entities, concepts, relationships, attributes) are identified with URIs, allowing data from different sources to merge without collisions. By doing this, you can align the same real-world entity used in different data sources. The most standard and powerful predicate used to establish mappings between multiple URIs of a single object is owl:sameAs.

Data Provenance

Tracking where data came from has so many important use cases. GraphDB maintains this level of detail. Users not only know the semantic facts but they know data sources, dates, levels of trust and other Metadata about the data.

Single interconnected information space formed by structured data and text documents.

It is based on materialised connections between free flowing, unstructured text, and data facts stored as database entities. These connections are extremely valuable as they link entities from the database to the documents that mention them denoting relationships from which they were extracted.When these connections exist, organizations can keep all of their data synchronized. The interconnected information space can be accessed through hybrid queries, combining the richness of the full-text search with the selectivity and precision of the databases.

Linked Open Data Compatibility

Hundreds of billions of World knowledge are available for free in the Linked Open Data world about music, places, subjects of interest and products. When applied correctly, semantic facts can enhance your knowledge management and data discovery applications.

Expressive, rich and flexible data model

Graph databases are often referred as schema-less, where there is no schema that defines how database is organized. GraphDB supports all forms of metadata classification of data, express as ontologies, where ontologies are equated but limited to thesauri, taxonomic hierarchies of classes, class definitions and relations.


GraphDB can infer new knowledge from existing facts. This is called inferencing. Why is this important? You can create new facts from existing facts. Your queries run faster. Your results are more accurate. Not all graph databases support this capability and some apply different techniques to infer new semantic facts. The applications of inferencing span industries and use cases. Knowing that two people are connected through a series of other factual relationships can be helpful in identifying networks for a variety of purposes – for example social networks, fraud networks or terrorist networks. In physician referrals and clinical trials research, the ability to infer a doctor’s specialty based on the drugs prescribed can help you find doctors that you require. When analyzing economic markets, the ability to infer trading price points for commodities using weather and regional data may provide you with a competitive advantage.

W3C standards compliance

For graph databases such as Resource Description Framework (RDF) and SPARQL query language. Unlike other proprietary NoSQL specifications, these standards are solid and have as much industry support as the basic specifications that make WWW work: HTTP and HTML. GraphDB stores semantic facts in the form of subject – predicate – object using the Resource Description Framework. RDF is a standard model for data publishing and interchange on the Web. RDF has features that facilitate data merging even if the underlying schemas differ. RDFS and OWL are its schema languages; SPARQL is the query language, similar to SQL. This ecosystem of standards is defined by the W3C consortium within community processes that involve all major data management vendors (IBM, ORACLE, HP, Microsoft, to name just few.


Probably the highest profile application of semantic technology to date, BBC’s 2010 World Cup web site is delivered using the OWLIM Enterprise semantic repository. A famous “call to action” by John O’Donovan (Chief Technical Architect, BBC) has spurred a flurry of semantic technology activity in world-known media companies, particularly in the UK and US.


KT Corporation (formerly Korea Telecom), is the leading South Korean integrated telecommunication service provider. KT has an information and communications business, and has the largest portion of the South Korean local telephone and high-speed Internet business. Megapass is a broadband telecommunication service offered by KT, featuring Interactive TV, TV-VOD (Video on Demand) and including movies and popular television programs, remote domestic video monitoring, SMS messaging, and local service ‘directory’ information.

Start with GraphDB



GraphDB Standard Edition

GraphDB™ Standard allows organizations to manage tens of billions of semantic triples on one commodity server
Ontotext Self-Serve Semantic Suit icon on GrapDB DBaaS Edition

GraphDB database-as-a-service is the perfect solution for scenarios with small or medium database size and query load, where investing in software licenses and provisioning and maintaining an on-premise 24/7 server is not cost optimal.

Ontotext offers five editions of GraphDB™:

Standard, Enterprise, Database-as-a-Service on S4Cloud on AWS and Lite.

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