How to Build a GrEAN Stack Application

There are all sorts of “stacks” out there… MEAN, WISP, LAMP. Today, I introduce you to a new one that I’m working on. — GrEAN. It stands for Graph – Express – Angular – Node.

The “Gr” in GrEAN is Graph, but what kinds of graph databases does that cover? Well, you can use a graphy graph like TinkerPop, GraphDB, or Neo4j. Or you can use a triplestore graph like SPARQL Server, AllegroGraph, Stardog, or Jena Fuseki. Either way, the application can be built exactly like a regular MEAN stack application. Just instead of using Mongo and Mongoose to store your data, you build your stuff with an ontology and graphs. And the cool thing is, it is very easy to rapidly prototype things with it, and the complexity of the kinds of filtering you can do is rad.

The other thing that’s great about graphs is that you can do all sorts of shape and path queries. Like, query on the richness of a cluster / subgraph. You can ask what the path between two facts is. You can ask how naturally-occurring is this structure. You can ask, what data can we infer that isn’t explicitly in the data set currently? You can ask questions against the ontology itself, if we know this person has symptom x, y, and z, what are all the possible medical conditions that person can have?

I’ve recently begun build GrEAN stack applications, and I’ll report back as soon as I get to another benchmark.

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