Radxa Rock (the article keeps talking about 'the Radxa' when that's the name of the company selling Radxa Rock, by the way) is similar to the various PC-on-a-stick, but in a development board form factor and with more I/Os and GPIO exposed.
Rockchip only provides support for Android and more recently Chrome OS, with GNU/Linux support being mostly community developed. The good news is that most hardware is working on GNU/Linux, with the exception of the video decoder and encoder (which is typical for most SoCs)and the NAND driver is closed source because it includes the flash translation layer which is treated as a trade secret by flash vendors. The bad news is that the kernel code developed by Rockchip is a bit crap and the community forks are quite fragmented because there's no central place to centralize various patches. Even so, it's generally straightforward to add support for a new board. We have a wiki[0] and an IRC channel - #linux-rockchip on Freenode if you're interested. The Radxa guys maintain their own fork so at least for their platform it's clear what to use.
I'd say it's a good choice for running Android or for hacking or for doing processing tasks (things like a building packages, running a low power webserver, continuous integration, etc) on GNU/Linux.
Some people in this thread ask/complain about platform-specific GNU/Linux distributions. There's Picuntu[1], but my view is that platform-specific distros are completely unnecessary and even a bit silly. On x86 you don't run Thinkpad-Ubuntu, you just run the generic Ubuntu. This is no different for ARM computers, you can use any generic distribution with a ARM port, with a kernel image compiled for your hardware and maybe one or two other drivers which need to be set up in userspace.
Compared to RPi, RK3188 (and other similar SoC) devices have a massive advantage since it's ARMv7 while RPi is ARMv6 which most distros don't support anymore. The difference in CPU performance compared to Raspberry can't be understated, it has 4 cores which are maybe 2 to 4 times faster for most workloads, about three times the memory bandwidth, four times the RAM, etc.