Announcing Ontotext GraphDB™ 6.2 with Workbench Enhancements

Latest enhancements to leading RDF graph database focus on ease of use, search capabilities and adding parallel inference

Sofia, Bulgaria (June 2, 2015) Ontotext, the developer of GraphDB™, has announced the release of GraphDB 6.2 with a major update that will allow customers to more easily make sense of their text and data. The enhancements are designed to get customers up and running faster with significant improvements to the usability of GraphDB Workbench, more robust FTS connectors and faster parallel inference capabilities.

GraphDB Workbench. The new GraphDB Workbench and Quick Start Guide make it easier than ever to get started using GraphDB. Import is now easier with configurable chunking and retry counts. To make writing SPARQL queries easier, syntax highlighting and automatic prefixing are available. Queries are now organized by tabs with permanent links to specific queries accessible in the browser’s address bar. New keyboard shortcuts, built-in result previews, filtering and integration with Google Charts are also included.

Connectors Support. GraphDB’s plug-in architecture allows for handling query types, such as full-text search (FTS), faceted search and geo-spatial, which cannot be handled efficiently with standard RDF indices. GraphDB Connectors are plug-ins for Lucene, Solr and Elasticsearch that allow SPARQL queries to utilize the FTS capabilities of these engines. They also update the indices after each update of the relevant data in the triplestore. The new transactional Entity Pool in version 6.2 allows multiple worker nodes in a GraphDB cluster to integrate with one and the same FTS engine instance. In the case of Solr and Elasticsearch this also enables FTS index partitioning across the worker nodes and thus better scalability and efficiency of search. Starting with GraphDB 6.2 the connector for Lucene is included in the Standard Edition; previously all connectors were available only in the Enterprise Edition.

Parallel Inference. Parallel inference allows forward-chaining (inference at the time data is entered) to be used more efficiently, even in scenarios with very big datasets. Today, GraphDB implements the only reasoning architecture that allows efficient and transparent reasoning to be applied across the entire life cycle of the data – from loading to querying and updates. Version 6.2 adds support for parallel inference that can be used through the LoadRDF tool to make bulk load up to 4 times faster.

“We have invested a great deal of resources in improving not only the functionality of GraphDB Workbench, but also the usability. More and more companies are realizing what a powerful tool RDF graph databases are to their businesses and we want them to be able to quickly and easily realize the benefits,” stated Atanas Kiryakov, CEO of Ontotext. “We are proud of the way our development team has listened to the needs of the market and responded with these updates in the latest version of GraphDB. Still, with GraphDB 6.2 we remain committed to delivering to the market the most robust triplestore that offers good performance across a very wide range of use cases.”

To try GraphDB visit www.ontotext.com/products/ontotext-graphdb and select a version to evaluate.

About Ontotext

Ontotext provides complete semantic platform transforming how organizations identify meaning across massive amounts of unstructured data. Ontotext blends text mining, powerful SPARQL queries, semantic annotation and semantic search with an RDF graph database (GraphDB™) that infers new meaning at scale. Ontotext S4, The Self Services Semantic Suite, allows developers to build text mining and semantic applications in the cloud.

GraphDB™ is the only native RDF triplestore with the ability to perform semantic inferencing at scale. Ontotext launched GraphDB™ as OWLIM in 2004 and the product has been successfully deployed by organizations around the world including the BBC and AstraZeneca.  GraphDB™ is available in three versions: GraphDB™ Lite is a free semantic repository that can manage up to 100 million RDF statements in-memory; GraphDB™ Standard has the ability to manage 10’s of billions of RDF statements on a single server, includes and full text search connectors and is also available in a cloud-based implementation; GraphDB™ Enterprise adds clustering capabilities.

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