I would argue that data structure and system architecture play much more of a role than language choice. Scylla's claims only make sense for datasets that are completely in-memory. Cassandra explicitly targets much larger than memory datasets, and so your bottleneck should be disk throughput not CPU. If you plan to keep everything in memory and just snapshot to disk, you should probably change your choice of data structures.
We're also talking about wide-area storage. Any latency from Go over C++ should be negligible: the Go GC is sub-ms latency now and will just get better [1] while for inter-DC network latency you can expect 50-2/300 ms latencies. The GC just doesn't matter here. Go also gives you control over memory layout, and has an ever-improving compiler [2]. C++ would only really be necessary for sub-ms tail latency systems which are really rare.
I think the gap between BigTable and Hbase is likely due to Google spending more time optimizing BigTable. They do use it for basically everything not built on Spanner.
[1] See recent activity on https://github.com/golang/go/issues/10958
[2] Go has a ways to match GCC, but you can work around the language for now to get close to C. If you want to improve things here, maybe contribute to gccgo or gollvm so Go users can get all of LLVM & GCC's optimizations.