Earlier quoted context omitted.
Most of these tools treat the "local file" as a stream which can be a pipe to a network stream from the object store. The files that are not streamed and need random access are often better on a local ephemeral SSDs or in RAM after a fetch of the, say, 50GB hash table, or whatever it is. At least, that's my experience: streams and in-RAM pre-processed DBs are >99% of file IO.
I didn't make my statement out of ignorance. Most of these applications depend on OS optimizations that have been made over the decades; multithreaded readers, readahead, and caching are critically important to read performance. In principle, a remote storage system could be as fast as a local disk. This includes random access. after all, the storage system is just a bunch of drives attached to machines connected by…
Even with potential optimizations, initiating a seek on GCS or S3 is far far slower than on a local SSD, so even if Google exposes fast cross-network seeks on objects inside an internal object store system, it is not readily accessible to the plebes like me and 99.9% of genomicists that use cloud systems or their own hardware.