Here’s the Graph Technology Landscape Graph, based on the amazing work from Janos Szendi-Varga. I took his basic CSV file, and imported it into a Google Sheet. Then I did some minor modelling changes and some data cleanup, and ended up with a model like this:


Once I had that, I was able to load the data pretty easily, using this import script, but because that import script uses APOC, I cannot use that mechanism in here. Suffice to say that I exported the data into a "cypher-only" import script, which is what we will use on this graphgist.

Let’s load the data

I will load the data with a cypher-only import script, and it’s about 700 lines (215 nodes, 496 relationships) that needs to get created. Here it goes:

Now we have the data in here, but we need to take a look.

Let’s look at the graph

Here’s the full graph as we have it now:

Now let’s do some simple querying

Find companies with "graph" in their name and their neighbours

Here’s the query:

match path = (n:Company)--()
where contains "Graph"
return path

And look at the results:

Find Neo4j and the neighbours of the neighbours

Here’s the query:

match path = (c:Company {name:"Neo4j"})-[*..2]-(n) return path

And look at the results:

And last but not least, let’s look at some pathfinding.

Paths between Neo4j and GraphAware.

Here’s the query:

match (c1:Company {name:"Neo4j"}), (c2:Company {name:"GraphAware"}),
path = allshortestpaths ((c1)-[*]-(c2))
return path

Lets look at the results:

Hopefully this was interesting.

Just a start…​

There are so many other things that we could look at. Use the console below to explore if you are interested in more.

I hope this gist was interesting for you, and that we will see each other soon.

This gist was created by Rik Van Bruggen