After the recent announcement of Amazon Nepture it became more apparent that Graph databases are becoming mainstream. This talk will provide an overview of graph databases and showcase how they can facilitate data integration tasks
Graph databases are becoming more mainstream day by day and terms like Neo4j, Gremlin or GraphQL are no longer unknown words for most developers. Recently, Amazon got into play by providing Nepture, a fully-managed graph database as a service which indicates that there is a big market demand. Graph databases provide a very agile way to store and query data with diverse schemas and, through this, facilitate data integration tasks. There are two general types of graphs: property graphs, and RDF graphs. Property graphs are mostly driven by industry standards (e.g. Gremlin query language) while RDF graphs are driven by W3C standards (e.g. RDF and SPARQL query language). This talk will provide an overview of both technologies and focus on how RDF and RDF databases can ease data integration in a loosely coupled manner.