Moreover, you’ll seamlessly transition from traditional relational databases and tabular data to the dynamic world of graph data structures that allow powerful, path-based analyses. As well as ...

You’ll be guided through how to transition from traditional relational databases and tabular data, to graph data structures that allow powerful, path-based analyses. What’s more, you’ll learn how to ...

Learn some basic database design principles and factors to help you choose the best data model for your project. Compare relational, document, graph, and key-value models.

A new semantic-based graph data model has emerged within the enterprise. This data model has all of the advantages of the relational data model, but goes even further in providing for more ...

Graph databases document the connections between data points rather than tables. Graph systems represent data not as elements in tables, but as nodes linked to one another by edges. Graph databases ...

Regarding my colleague's reference to Stonebraker's seminal 2006 paper that refutes "one size fits all" DBMS architectures, their anecdote that Neo4j arose from their attempt to use a relational DBMS ...

Graphs have become increasingly integral to powering the products and services we use in our daily lives, driving social media, online shopping recommendations, and even fraud detection. With this ...

This will teach you the tricks of the profession from two practising Graph Data Scientists. Learn how to work with graph data, to building recommendation systems using simple and more complicated ...

The development of database technology is one of the defining achievements of the information technology era. Relational technologies originated in the 1960s and 1970s, and were characterized by a ...