[handrous]

Neo4j is all-in on, "almost everything looks like (or can be made to look like) a graph, so almost everyone should be using a graph database".

As for those specific figures, I'm guessing there's enough wiggle room in "data and analytics innovations" (emphasis mine) to find or project almost any trend one wishes. What are data analytics innovations? Why, it's the set of things that will see 80% use of graph technologies! "Graph technologies" is also so potentially-vague that it could plausibly be 100% of almost anything related to software.

[vincent-toups]

"Everything looks like a graph" is more damning of the idea of a graph as storage than it is praise. The whole point of a database is to impose _additional_ constraints on the data to ease subsequent application development or data analysis.

Relational data may be a hassle but its a hassle you end up having to deal with anyway at some point.

I can see a graph database as being a useful place to stash a ton of shitty data as an initial place to start an ETL but I can't imagine using it as a system of record except in very limited situations.

[ants_a]

The additional constraints are also what enable performance optimizations. And not the small ones, the ones that give orders of magnitude improvements. Whereas right now neo4j is slower for graphs than postgres, just with a nicer UI.

[handrous]

Oh, I agree that, baring some actual honest-to-god innovation, the whole product category's niche-by-nature. Just relating the way Neo4j's been positioning themselves.

[redbar0n]

the point is that "to ease subsequent application development or data analysis" can be done just as well, or better, by a graph DB. You don't have to end up with the hassle of relational data as in an RDBMS.