Graph databases are poised to expand dramatically in the next few years as the nature of what is important and worth saving in an enterprise has expanded dramatically beyond alphanumeric data and into relationships.Mcknight highlights interesting use cases:
My graph database client, in retail, uses the social graph for churn management and for developing promotion lists. Finance graph uses I know about include churn as well, but also investigating corruption and fraud and how trades and other series of events are related. Social networks are the obvious fit. When a telecommunications customer leaves a vendor, his or her peer group is highly susceptible to do the same. Intervention is required at this point. Similarly, receptivity to promotion tends to be shared across the social network. Configurations and recommendations can also have complex relationships that require a graph database to return relationship inquiries with high performance.He summarizes, “when you are considering your NoSQL needs, you have to consider the asterisk after ‘big data.’ Graph databases are out to change your relationship with NoSQL projects.” Read the full article.