The implementation you are discussing sounds pretty elegant. I am most familiar with Power BI from a data viz perspective, but have used most of the enterprise viz tools out there.
The thing that always struck me about Power BI (and also Qlik) is that it is very much a model-first tool. Visualization is secondary to the model, to the extent that much of the friction I see in new users has been treating it as a reporting/layout/visualization tool when, in fact, it is a data modeling tool with a visualization engine strapped on.
One of the big drawbacks with Power BI is that it has a terribly inefficient implementation for propagating filter contexts for visual interactions (this is their translation of your "auto interactivity, which propagates data (dimensions) pulse along the network"). I do not know the internal implementation, but I am relatively certain that visual interactions are ~O(N!) in the number of visual elements on a report page, based on my experience of performance scaling across a wide range of reports. Regardless, one of the best practices is to limit a Power BI report page to a small number of visualizations (recommendations of the cutoff value vary, and types of visuals can also impact this).
If I understand you correctly, you are calculating the minimum set of recalculations/re-renderings necessary, based on the data element that a user has interacted with. This should be something much closer to O(N) in the number of visuals to propagate user selections to other visuals. I am making an assumption that most visuals should interact, as typically the scope of a single report should have a high degree of intersection of dimensionality across all report elements.
I do not know of any analytics engine that exposes the sort of DAG and associated API you are discussing, either. The reason for my initial question was simply because that sort of engine is a product in and of itself. There are plenty of columnstore databases (and following other paradigms, but optimized for OLAP workloads) out there. It seems like biting off a lot to tackle both the data engine and the visualization tier at the same time.
The big reason that I ask is that this sort of approach to visualization seems to me to benefit greatly from a data model that supports transaction-level detail. The type of interactivity that you expose is extremely powerful. I have seen interactive tools hamstrung by data models that do not allow sufficient interaction. As soon as you put interactivity in front of users, in my experience, they want to do more with the data. If you are limited to datasets that can live comfortably in the browser, that seems a showstopper to me, as it will require pre-aggregation to fit most of the datasets I've seen; pre-aggregation negates many benefits of interactive data exploration.
I'll be taking a much further dive into your product either this weekend or next. I'm very interested.