Graph databases rely on graphic structures and semantic queries that feature nodes, edges and properties to display and store data. Unlike relationship database, the relationships between the available records are stored directly. Therefore, graph databases make it easier to retrieve complex hierarchical structures.
GraphDB relies on SPARQL queries, text mining as well as semantic annotations and advanced search to infer new meaning at scale across massive amounts of unstructured data. Consequentially, it can be a great starter tool for companies that are interested in implementing smart data proof-of-concept.
The utility acts as a Storage and Inference Layer for Sesame and this is why it makes extensive use of the latter's architecture and features. The API is implemented seamlessly with the rest of the Sesame framework, so that developers are able to design user interfaces directly. Users can manipulate the repository generated through the embedded workbench as well as other tools that are commonly integrated with Sesame.
The Free edition of the graph database management tool is suitable for massive volumes of data and is designed as an enterprise-grade semantic repository system. However, it mostly addresses smaller projects that entail low query loads, as it can scale to around 10 billion RDF statements on a single server and has certain limitation regarding the number of concurrent queries it can perform.
It cannot handle more than two queries in parallel
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