From graph theory through the history of computing and how it affected database design, to why relational databases aren’t about relations. Next, a look at how diverse the current graph database market is and what obvious and not so obvious problems are solved by graphs. We will see how to launder money, suggest products, give answers to NLP tasks, build a knowledge base, balance a game economy and model mixed concept domains. A short introduction to Neo4j’s query language, Cypher, will show the main concepts of querying graph data. Then, by use of the same datasets in both relational and graph databases will compare syntactic clarity and database performance.
With .NET from version 1.1 and with web development from the time when
IE6 was the “better” browser. Now a chief architect in ITMAGINATION
leading a 45+ developer project by day, and a proud developer
of cookit.pl, a pet project processing hundred
of gigabytes of data with whatever suits the problem best (Graph
databases/ML/C#/F#). Technology enthusiast, speaker, and blogger
at IndexOutOfRange.com.
