Excerpt from article posted on Forbes
“Master Data Management innovators use graph databases to ask new questions and discover new answers within their existing data,” explained Emil Eifrem, CEO and co-founder of Neo Technology, makers Neo4j, the most popular graph database. “They are finally achieving that desirable 360-degree view of the customer in real time.”
The problem is that we are leaving valuable information on the table when we think of MDM as a synchronized repository. The world of MDM is essentially defined by the sort of primary key relationships that are used to connect relational databases. For the customer record, often the social security number becomes the key and we can easily use it to grab the master records for a customer from the master repository or from a business system.
Here’s where the glory of graph databases starts to emerge for MDM. If we now look at the collection of customer master records, what else can we find out about them. Graph databases treat the connections between two pieces of information as a first class object. This means that you cannot only search and categorize data by the fields, but also by the relationships between the data.
For example for customer data, a graph database can quickly tell you all the customers that bought the same products that live in the same state that are the same age. You can then quickly find all the customers that didn’t buy the product but are in the same state and the same age. It’s not that you couldn’t eventually ask and answer the same question using a relational model. You could. The problem is that the complexity of the query you would have to write and the effort involved makes it harder to answer important questions.