Highly Connected Data Models in NOSQL Stores by Jim Webber.
From the description:
In this talks, we\’ll talk about the key ideas of NOSQL databases, including motivating similarities and more importantly their different strengths and weaknesses. In more depth, we’ll focus on the characteristics of graph stores for connected data and the kinds of problems for which they are best suited. To reinforce how useful graph stores are, we provide a rapid, code-focussed example using Neo4j covering the basics of graph stores, and the APIs for manipulating and traversing graphs. We\’ll then use this knowledge to explore the Doctor Who universe, using graph databases to infer useful knowledge from connected, semi-structured data. We conclude with a discussion of when different kinds of NOSQL stores are most appropriate the enterprise.
Deeply amusing and informative presentation.
Perhaps the most telling point was deciding between relational and graph database usage, based on the sparseness of the relational table. If sparse, don’t have “square data” and so probably better off with graph database.
Saw this in a tweet by Savas Pavastatidis.