I meant that products like Esper, StreamBase, InfoSphere have been around for a long time, which have a _very_ rich set of features [1], and are mostly designed around single process usage. Lot of the type of queries they support are not possible to implement in a performant way in a distributed system. Though nowadays Esper claim to have horizontal scalability - it was originally designed as a single threaded system. They do also have a passive/active type solution as you mentioned.
Stream processing frameworks originally evolved to offer "big scale" through data partitioning compared to the traditional CEP systems. But CEP engines have been able to deal with windowing and similar concepts since many years ago - the main difference of the stream processing frameworks _is_ the distribution and scalability aspect.
My point was that the systems linked in the original article seem to match closely to the limitations of what distributed stream processing frameworks are able to do, but only run on a single node.