Firstly, there were features. Tighter integration with OWL and schema-awareness was something we wanted to build in at a low level. We also wanted to leverage CLP(fd) for time and other range queries. If we were going to need to fundamentally alter the semantics anyhow, it didn't seem that important to start with SPARQL. Other features that are coming down the pipes very soon are access to recursive queries and manipulation of paths through the graph.
Secondly, we wanted better composability. One of the real strengths of SQL as a language is that it is very easy to compose language elements. By contrast SPARQL feels quite ad-hoc, mimicing some of the style of SQL but losing this feature.
Lastly, we wanted to have a language which would be easy to compose from Javascript, or python. Javascript, because we live in a web age, and python, because it's the choice for many datascientists. JSON-LD provides a nice intermediate language in which to write queries in either of these languages. No need to paste together strings! And then, because of the choice of JSON-LD, we can naturally store our queries in the graph (and even query our queries).