No mention of Apache Spark? Thinking about where Spark would fit in here, because it has both structured and unstructured APIs--I think it would fall under most of these categories depending how you use, going back to the comment in the article:
> Most of these systems are equally expressive and can emulate each other
But a quick stab at how I think it could fall under this taxonomy:
[structured]
If using the DataFrame API
[unstructured]
If using the DStream API
---
[low temporal locality]
If you don't watermark and let the state grow--which I don't have much experience with,
but I think could possibly run into scalability issues, you'd have to write some
imperative logic to cull state--but it's very necessary for low temporal locality.
[high temporal locality]
If using watermarks, it will close the and take the output for you
---
[internally consistent / internally inconsistent]
Not really sure how Spark falls here, I think if you use the DataFrame API, you can have
it be consistent, but a lot of operations aren't supported, so you may end up having to
switch to DStreams and write code imperatively.
And then further, what if one of the streams is processed faster than each the other in
an aggregation? I'm not sure if there's a way to specific business rules around making
things atomic--but I'm sure you could hack it if you dropped low level enough.
I think this is touched upon in the other article:
> When combining multiple streams it's important to synchronize them so that the outputs
> of each reflect the same set of inputs.
That said, I'm really excited by the future of Spark Structured Streaming--I want to write declarative code and say how my data gets from A to B--not what needs to happen to get from A to B.