Should have tackled this in my other post. But, let me approach this question from two angles.
Is it worth paying $20K for any DB or DB support? If it would save you 1/10th of an engineer per year, it becomes immediately worth. That means, can you avoid 5 weeks of one SWE by using a DB designed to better suit your dataset? If the answer is yes (and most cases it is), then absolutely that price is worth. See my blog post about how much money it must be costing big companies building their graph layers.
Second part is, is Dgraph worth paying for compared to Neo or others? Note that the price is for our enterprise features and support. Not for using the DB itself. Many companies run a 6-node or a 12-node distributed/replicated Dgraph cluster and we only learn that much later when they're close to pushing it into production and need support. They don't need to pay for it, the distributed/replicated/transactional architecture of Dgraph is all open source.
How much would it cost if one were to run a distributed/replicated setup of another graph DB? Is it even possible, can it execute and perform well? And, when you add support to that, what's the cost?
I have no doubt, when you consider the factors of scalability, Dgraph comes out much cheaper.
I haven't looked at DGraph much but if they are trying to store the graph in a distributed manner then the use-cases will be different.
From experience, using GrapheneDB/Neo4j takes much less than 1/10th of an engineer / year to manage, so unless your data doesn't fit in 1 box you'd be better off with Neo4j
20k per year seems like an incredibly reasonable price for a managed distributed cloud store, especially when considering maintenance cost.
This ignores second-order effects.
Is it worth limiting yourself to an ecosystem with only users who are ok paying $20k per year, with "open source" development but all development activity done by one company that is trying to make a profit off something unproven, and then tie your core business data to it? Maybe. Not so clear cut though.