The latest version GraphDB 8.3, released just two months after the previous release is focused on cluster and connectors improvements. We crafted this version to make the experience of working with our semantic graph database better, faster and easier.
New York, USA (PRWEB) September 07, 2017
Between the beginning of 2013 and October 2016, the demand for Graph databases has increased 6 times. DB-Engines’ complete trend of database systems popularity shows that since January 2013 graph databases have been growing in recognition more than any other database management systems.
According to Ontotext, who develops the leading Semantic Graph Database GraphDB ™, their surge in popularity has been driven by 5 key characteristics, which grouped under the acronym S.M.A.R.T. - speed, meaning, answers, relationships, and transformation.
Speed - With data and information all around us piling by the second, the speed with which enterprises can analyze their data is essential for reducing costs and the time employed in making sense of various data sets of both proprietary and open sources.
Meaning – The way graph databases organize and store information helps to maintain the connectedness of multiple entities enabling computers to interpret related items in a context instead of just matching words. Thus machines, just like human’s brains, are able to store, manage and retrieve information based on meaning and logical relations.
Answers - The meaning attached to the entities allows graph databases to answer questions that go far beyond what can be found with simple keywords. Behind their capability to answer intricate questions when dealing with complex and highly interconnected data, is the fact that graph database technologies use one essential characteristic of the Semantic Web – relationships.
Relationships – By representing the connections among billions of entities, graph databases help to explore both apparent and hidden relationship, for example, how one person is connected to another, to a certain place or organization and many more. In today’s exponentially growing data world, this offers organizations a unique chance to see their proprietary data from different angles and even to connect it to external sources and reveal further relationships.
Transformation - Graph databases have the potential to drive innovation and transform enterprise data management into an interconnected all-round view of all data sets. They have an incredible impact on the way the Institutions and enterprises are beginning to look at their data and use the power of semantic technology to link and integrate their most precious resources – their content.
As a pioneer in the Semantic Technologies, Ontotext - the company developing the leading Semantic Graph Database GraphDB ™, recognizes the need for big enterprises to publish their data internally and externally.
This establishes GraphDB ™ as the paradigm of choice for metadata and master data management in the biggest international companies.
Following the user’s feedback, Ontotext is releasing the latest, 8.3, version of its signature semantic graph database, GraphDB ™.
The most noticeable usability improvement in its visual environment is the simplified table-to-RDF transformation process. Next, the default graph visualization can be configured with the full expressivity of the SPARQL language to control the displayed graph data.
The new CTO of Ontotext Vassil Momtchev said:
“The latest version GraphDB 8.3, released just two months after the previous release is focused on cluster and connectors improvements. We crafted this version to make the experience of working with our semantic graph database better, faster and easier.”
The GraphDB 8.3 release comes with an upgrade to the latest RDF4J public release and various bug fixes.
For over a decade Ontotext has brought together metadata and content to search, navigate and analyze information in more productive ways. Ontotext was among the first organizations in the world to recognize the power of semantic-driven technology. After extensive product development and self-funded R&D, Ontotext's vision for semantic technology is now being shared by some of the world's most renowned organizations spanning a diverse range of industries.
Company client list includes news and media agencies like the BBC, Press Association and Financial Times, top Academic publishers like Springer Nature, Elsevier, IET, Wiley and Oxford University Press, leading pharmacological companies such as AstraZeneca, important government agencies including the US Department of Defense, The National Archive of UK, US Medicare, and centuries old cultural institutions like the British Museum.