Over time, most likely, graph databases will become as commonplace as relational databases are today. Allied to this is the rise of graph data query languages like Cypher, which was recently made ...

More and more systems are also enabling relational shims that hide the details of the differences between tabular and graph databases so that they can work with existing toolsets (such as those ...

Learn the key differences between relational and NoSQL databases with this in-depth comparison. There’s nothing wrong with the traditional relational database management system. In fact, many ...

As convincing as the contextualization of data in semantic graph databases is when conducting analytics at scale, it is perhaps more compelling to consider the ease with which such queries are issued.

Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it ...

While they used this to compare AnzoGraph (an OLAP graph database) to Neo4j (an OLTP graph database), they admitted that the comparison was unfair, and I decline to print that here.

A graph database is a dynamic database management system uniquely structured to manage complex and interconnected data. Unlike traditional databases organized in rows and columns, graph databases ...

Graph databases are increasingly popular. In fact, according to DB-Engines graphs are the fastest growing of any database category since 2013. This growth is fueled in part because many organizations ...

Second, I’ll share some key business use cases that cannot be solved with traditional relational data catalogs. Finally, I’ll wrap it up by getting technical and walking through a sample ontology, ...

Last week at SapphireNow I had a great chat with Lloyd Palfrey, a senor technical architect with Bluefin Solutions, one of the leading SAP services firms. I caught up with Lloyd at the bar (where the ...