Enrollment Nerdery

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Using DiagrammeR to help with Data Modeling in Neo4j

I have been watching the DiagrammeR package for a while now, and at this stage, it’s pretty impressive. I encourage you to take a look at what is possible, but be assured the framework is there to do some really awesome things.

One use-case that applies to me is that of data modeling an app within Neo4j. There are already some tools out there, namely:

The last link above is a sample graph gist that is a decent overview.

In this post, however, I am going to demo the idea that you can use DiagrammeR to assist in the data modeling process. The benefits, in my opinion, are:

A Basic Model

The code and data model below are intended to highlight a simple proof-of-concept about how you might leverage graphViz to make the data-modeling tasks in Neo4j easier.

      digraph neo4j {
      # a 'graph' statement
      graph [overlap = false, fontsize = 10]
      # several 'node' statements
      node [shape = circle, fontname = Helvetica]
      a [label = 'Student']; 
      b [label = '@@1-1'];
      c [label = '@@1-2'];
      d [label = '@@1-3'];
      e [label = '@@1-4'];
      f [label = '@@1-5'];
      g [label = 'Marketing Persona'];
      h [label = 'Gender'];
      i [label = 'State'];
      j [label = 'Region'];
      k [label = '@@2-1'];
      l [label = '@@2-2'];
      m [label = '@@2-3'];
      n [label = '@@2-4'];
      # several 'edge' statements
      a -> b [label = 'WAS_SENT' fontsize = 9.5];
      b -> c [label = 'NEXT'];
      c -> d [label = 'NEXT'];
      d -> e [label = 'NEXT'];
      e -> f [label = 'NEXT'];
      a -> g [label = 'FROM_PERSONA'];
      a -> h [label = 'HAS_GENDER'];
      a -> i [label = 'LIVES_IN'];
      i -> j [label = 'IS_IN'];
      a -> k [label = 'HAS_INTERACTION' fontsize = 9.5];
      k -> l [label = 'NEXT'];
      l -> m [label = 'NEXT'];
      m -> n [label = 'NEXT'];
      [1]: rep('Email', 5)
      [2]: rep('Interaction', 4)
engine = "circo")


From above, a few things that I wanted to call out:


By no means is this a robust demonstration, but simply a quick post to demonstrate an option that you might want to leverage when documenting and building out your database. As mentioned above, the fact that you can reproduce your graph is why I will probably use DiagrammeR to work through my data modeling tasks.

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