GraphDB Storing Engine
The GraphDB Suite provides the GraphDB storing engine to save and use ultra-large graph data of over 10 billion triples. The GraphDB storing engine provides the axiom in 3.3.2.3 for high-level and low-level reasoning, relationship reasoning, and verification between concepts. Through the axiom, a new fact can be created and saved.
The GraphDB Suite supports W3C‘s graph models such as RDFS, OWL, and OWL2. The (Labeled) Property Graph model can be saved and queried through the Apache TinkerPop and Gremlin server linkage. Users can use two data models selectively according to their purpose.
The GraphDB storing engine offers a query language for searching, modifying, and deleting data. The engine provides W3C’s SPARQL and GraphQL, which can be accessed easily and promptly through REST-based API for data opening, sharing, and analysis.
Introduction
The GraphDB storing engine provides the repository function for storing RDF-based graph data and the Property Graph. This engine also provides the function to save and analyze the Property Graph through the linkage with Apache TinkerPop and Gremlin server. RDF-based graph data is presented as triples while the Property Graph is presented as Vertex and Edge, which can have a property.
Main Features
Main Functions and Specifications
- Large-scale graph data storing function
The graph data storing function allows the promptly loading (parsing, validation) of large-scale graph data. This function supports various graph data formats (RDF/XML, N-TRIPLE, Turtle, etc.). When loaded, it simultaneously saves reasoning results through systematic linkage with the reasoning engine. This function also guarantees prompt and stable graph data change.
① Powerful transaction function
② Various interfaces for data loading
③ Graph data export function (Exporting Graph Data)
- JENA and graph data framework
GraphDB provides graph data repository creation and access through JENA API. Thanks to that, an application that accesses GraphDB remotely can use most functions provided by JENA API. JENA, the semantic framework, is the most frequently used framework worldwide. This framework provides model and query interfaces that allow anyone to use graph data easily and promptly.
- Graph data management function
The graph data management function consists of functions that include graph data repository setting and management, data loading, query management testing, index generation, and management for various analyses, plug-ins, and server monitoring.
① Project management function
② Graph data query management and test function
③ GraphDB data management and edit function
④ User management and monitoring function
- SPARQL query function
GraphDB provides graph query languages (GraphQL, SPARQL) for inquiring graph data. SPARQL Endpoint is the W3C’s standard protocol to access the REST-based knowledge graph data set. SPARQL is the standard RDF-based graph data query language used for interacting with RDF-based graph databases. SPARQL updates are provided through SPARQL1.1 support.
The REST-based SPARQL Endpoint provides the following HTTP protocol. The parameters for requests and responses according to the SPARQL’s query type are provided. In general, RDF/XML and RDF/JSON types are the most frequently used.
Main engine screen
