GraphDB Fundamentals

GraphDB Fundamentals builds the bases for working with graph databases that implement the W3C standards and particularly GraphDB. It is a training class delivered in a series of ten videos that will accompany you in your first steps of using triplestore graph databases.

Module 1: RDF & RDFS

RDF is a standardized format for graph data representation. This module introduces RDF, what RDFS adds to it, and how to use it by easy-to-follow examples from “The Flintstones” cartoon.

Module 2: SPARQL

SPARQL is a SQL-like query language for RDF data. It is recognized as one of the key tools of the Semantic technology and was made a standard by W3C. This module covers the basis of SPARQL, sufficient to create you first RDF graph and run you first SPARQL queries.

Module 3: Ontology

This module looks at Ontologies: what is ontology; what kind of resources does it describe; and what are the benefits of using ontologies. Ontologies are the core of how we model knowledge semantically. They are part of all Linked Data sets.

Module 4: GraphDB Installation

This video guides you through five steps in setting up your GraphDB: from downloading and deploying war files to your Tomcat Application Server, through launching Workbench, to final creation of a database and inserting and selecting data in it. Our favorite example from The Flintstones is available here as data for you to start with.

Module 5: Performance Tuning & Scalability

This module provides information on how to configure GraphDB for optimal performance and scalability. The size of datasets and the specific use cases benefit from different GraphDB memory configurations.

Watch this video to learn more about the four elements you can control as well as how to use GraphDB configuration tool. Tips about memory dedication during loading time and normal operation are provided as well.

Module 6: GraphDB Workbench & RDF4J

GraphDB Workbench is a web-based administration tool that allows you to manage GraphDB repositories, load and export data, monitor query execution, developing and executing queries, managing connectors and users. In this video, we provide brief overview of the main functionality that you will be using most of the time.

Module 7: Loading Data

Data is the most valuable asset and GraphDB is designed to store and enhance it. This module shows you how to use GraphDB Workbench to load individual files and bulk data from directories. For huge datasets, we recommend speeding up the process by using Parallel bulk loader.

Module 8: Rule Set & Reasoning Strategies

This module outlines the reasoning strategies (how to get new information from your data) as well as the rule set that are used by GraphDB. The three different reasoning strategies that are discussed are: forward chaining, backward chaining, hybrid chaining. They support various GraphDB Reasoning optimization, e.g., using owl:sameAs.

Module 9: Extensions

This module presents three extensions that empower GraphDB queries:


calculates connectives of notes – similar to the well-known PageRank algorithm.


queries extract data placed in rectangles, polygons, and circles.

Full-text search

provides faster access to textual data based on Apache Lucene, Solr, and Elasticsearch.

Module 10: Troubleshooting

This module covers troubleshooting some common issues. These include both installation and operational issues. Installation issues covered include: Workbench, Lucene, Informatiq, and custom rule files. Operational issues covered include: statement counts, deleting statements, and socket timeouts.