Is there any downside/risk to using fst to compress a serialized list?

Question

The fst package http://www.fstpackage.org/fst/ offers multithreaded compression and reading and writing for data frames.

I'm running Bayesian models with brms that are large and slow. I want to save the results to disk for future re-use. Using saveRDS() with compress = "xz" they are ~200MB on disk and, of course, take forever to compress, and a lot of time to read in and decompress.

fst implements fast, multithreaded zstd compression.

x <- list(
  a = mtcars,
  b = as.POSIXlt("2021-01-01 14:00:05"))

saveRDS(compress_fst(serialize(x, NULL), compression = 100),
  file = "test_fst.RDS")

x2 <- unserialize(decompress_fst(readRDS("test_fst.RDS")))

all.equal(x, x2)

Returns TRUE and the other quick tests I have done suggest that this all works fine.

Am I missing any downsides or drawbacks to taking an arbitrary R object, serializing it, passing it to compress_fst() and then writing the compressed object to disk?