Ontotext GraphDB (original) (raw)
Link diverse business data, index it for semantic search, and enrich it via text analysis. Unlock insights and turn information into business knowledge.
The premier choice for scalable RDF databases efficiently handling graph analytics and semantic metadata management.
Unify data and add context with ontologies and linking to a global knowledge
Break down data silos, unify data sources and accelerate insight, analytics and market readiness using the only RDF engine audited on the LDBC Social Network Analysis Benchmark.
Manage and navigate data visually, create graph results, get more relevant search results and recommendations across data sources.
Understand datasets by exploring connections, context, semantics and relationships across entities and concepts.
GraphDB business applications
Data management
Consolidate volumes of domain knowledge about companies, electrical networks, products descriptions, scientific publications, etc. to ensure unlocking siloed information.
Content management
Utilize and repackage your information better to maximize content strategy efforts.
Business process management (BPM) & automation
Gain a holistic view of global business operations across complex systems such as building automation systems, automotive manufacturing, and aerospace.
CRM, PR, compliance
Strengthen media monitoring practices for PR, reputation management, and market research endeavors.
"GraphDB: Relatively robust. Ease of use for developing queries. Offer free features that could help the widespread use."
"GraphDB: The class hierarchy, class relationships, visual graph these options are great to know about ontology of data and relationship of data."
"GraphDB: I'm impressed with its performance and ease to use. I also appreciate the scalability as it has easily accommodated my growing datasets without sacrificing speed or reliability."
"GraphDB: Visualization of the graph SPARQL query interface. Easy importing and exporting. Multiple output formats available."
"GraphDB: Graphical relations are organized and presented in multiple meaningful ways. I am yet to encounter any performance issues, but I have only worked with the free edition."
"GraphDB: Visualization, creating and executing SPARQL queries, inference, supporting all RDF languages. There is a free edition available."
"GraphDB: It's efficient and very much as per our requirement. Totally love the product and planning to use it with more solutions."
"GraphDB is known for high performance. It can handle large amount of data and can process queries very quickly, which makes it very suitable for use in large-scale applications."
Industry leaders trust us
Try GraphDB
The ultimate RDF graph database, connecting diverse enterprise data, enriching it for semantic search, and revealing valuable insights.
With GraphDB, you can:
- Unify enterprise data from different sources to transform it from information into actionable knowledge.
- Enter natural language queries to talk with your knowledge graphs.
- Extract patterns and analytics from siloed information for deeper insights.
- Expedite data-driven decisions, reducing risk and cost.
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Which GraphDB Edition is right for you?
Start free or call us for custom pricing tailored to your needs
The most versatile RDF database
| GraphDB Free | GraphDB Enterprise | | | ------------------------------------------------------------------------------------- | ------------------ | | | Fully compliant with RDF 1.1 and SPARQL 1.1, with RDF-Star and SPARQL-Star extensions | | | | Fully compliant reasoning for the standard rulesets RDFS, OWL 2 RL and QL | | | | Custom reasoning and consistency checking rulesets | | | | 100% compatible with the RDF4J framework | | | | Easy to deploy anywhere using Java | | |
The best performance
| GraphDB Free | GraphDB Enterprise | | | -------------------------------------------------------------------------------------------------- | ------------------ | | | Highly performant simultaneous load, query and inference | | | | Ultra fast forward-chaining reasoning with efficient retraction of inferred statements upon update | | |
More than RDF
| GraphDB Free | GraphDB Enterprise | | | ------------------------------------------------------------------------------------------------------- | ------------------ | | | Plugin API for engine extensions | | | | Many plugins providing additional functionality such as geo-spatial indexing, GeoSPARQL, RDF rank, etc. | | | | MongoDB connector | | | | Lucene connector for full-text search | | | | Solr connector for full-text search | | | | Elasticsearch connector for full-text search | | | | Kafka connector for downstream synchronization | | |
High availability cluster
| GraphDB Free | GraphDB Enterprise | | | ------------------------------------------------------------------------------------------------------------------------- | ------------------ | | | Automatic failover, synchronization and load balancing to maximize node utilization | | | | Scaling out concurrent query processing, allowing query throughput to scale proportionally to the number of cluster nodes | | | | Cluster elasticity remaining fully functional in the event of failing nodes | | |
Convenience
| GraphDB Free | GraphDB Enterprise | | | -------------------------------------------------------------------------------- | ------------------ | | | Workbench interface to manage repositories, data, user accounts and access roles | | | | Community support | | | | Commercial SLA (optional) | | |
- GraphDB Free comes with a single-core license.
- GraphDB EE can be licensed to two or more cores according to needs and is available on-premise from Ontotext and its partners.
- The GraphDB Enterprise Edition 12-core cluster is also available as a software as a service (SaaS) on AWS Marketplace, Microsoft Azure Marketplace and Google Cloud Platform Marketplace.
Success stories
FAQs
Have questions? We’re here to help.
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No, this is a self-paced learning path experience with free access. You will need to register for the learning system.
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There are a couple of advantages to the Academy compared to the freely available Ontotext documentation and webinars. These training paths are designed with a specific audience profile in mind:
- Knowledge Graph Engineers, who are designing the data models with RDFS and maybe OWL, extending standard data models if necessary, developing SHACL shapes to ensure data quality, and identifying which data sets should be combined to create knowledge graphs for their enterprise’s applications.
- Application Developers who are using their JavaScript framework, or their preferred programming language, to efficiently query, add data to, and delete data from knowledge graphs stored in GraphDB on the backend of their system. They are not interested in rich ontology modeling, but they want to know about the various APIs that GraphDB supports and which are best for what.
- DevOps staff, who want to know how to configure a set of clusters to support the applications created by the developers, especially if those applications are being used by thousands of users. Question text goes here
This training is meant to provide data scientists, researchers, product managers and developers with the theoretical and practical knowledge necessary to design a small proof-of-concept project that demonstrates the utility of Semantic Technology and a graph database.
Although you will need to have some basic understanding of Semantic Technology and programming and query languages, no detailed knowledge is required. All advanced concepts exposed in the training will be explained in sufficient detail.
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Each learning path consists of three or four courses, and each course typically takes a half a day or a little more.
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