Early on when we first started playing around with General Processing on GPU's we had Nvidia cards to begin with and I started looking at the apis that were available to me.
The CUDA ones were easier for me to get started, had tons of learning content that Nvidia provided, and were more performant on the cards that I had at the time compared to other options. So we built up lots of expertise in this specific way of coding for GPUS. We also found time and time again that it was faster than opencl for what we were trying to do and the hardware available to us on cloud providers was Nvidia GPUs.
The second answer to this question is that blazingsql is part of a greater ecosystem. rapids.ai and the largest contributor by far is Nvidia. We are really happy to be working with their developers to grow this eco system and that means that the technology will probably be CUDA only unless we somehow program "backends" like they did with thrust but that would be eons away from now.