+1 Insightful. In fact, there's research toward showing the two are equivalent in possibility space of what can be represented/queried (https://arxiv.org/abs/1102.1889)

But yes, linked data and graphs are super powerful once the data is triplified. Suddenly you have an abstraction above the contents of your data into the 'shape' of your data.

SPARQL and RDF aren't going away, but they're the academic thing that I and others are trying to make useful. GraphQL is scratching the surface, but it's super exciting that it's scratching at all, imo.

(Disclosure: Founded CayleyGraph, supporting the open source https://github.com/cayleygraph/cayley, which I maintain and mostly wrote)

GraphQL, though, is a bit of a lie nomenclature-wise. As I've experienced it, it's got nothing much to do with graphs, at least not in the sense that SPARQL deals with triples that form a graph. In this department I am really interested in TinkerPop [0].

I would love, some day, to spend some more time with triple stores, RDF and semantic technologies.

[0] http://tinkerpop.apache.org/docs/current/reference/

You might really enjoy datomic (www.datomic.com). Everything is stored as entity attribute value time and you query with a dialect of datalog. You can check out www.learndatalogtoday.org to get a flavor.

Datomic, though, isn't Datalog syntax at all.

I've got nothing against Datomic, but can't help to think learndatalogtoday is outright false advertising by trying to capture "Datalog" as SEO term for a proprietary graph database which has nothing to do with Datalog/Prolog.

The point of Datalog is that it's a subset of Prolog syntax, implying that engines can be reasonably exchanged for one another. But this is only possible with real Datalog, or SPARQL for that matter.

Prolog and datalog ae really high on my list. Thanks for the reminder!

Datomic, though... wish there was an OSS version or CE or something.