Choosing efficient output format for spatial data in R

Performance might be very dependent on data structure and size, complexity of geometry vs attributes etc. A very multi-dimensional problem space--consequently, no straightforward, general approach.

In your use case: GeoPackage. Can store several sets of spatial features in one file, can also store non-spatial tables as well, few constraints on column name length, well-supported and an open specification. Can use SQL to select subsets at load time. All good stuff.

But there's one other option if all you care about is getting this data back into R, and that's to save each set of features as an .RDS file using saveRDS. It's not OGR so you can't load it into anything else, but it would probably be the most efficient R -> files -> R only round-trip solution.

Note that most of the OGR formats are either limited in functionality and/or derived from vendor-specific formats. I would only use GeoPackages for saving spatial data to disk now, unless I had an end-user with a desperate and unfixable need for something else, such as a shapefile, or a web-oriented application that needed a GeoJSON file (which is practically limited to WGS84 coordinates) or I needed to load it into a GPS receiver in which case I'd probably have to use GPX (but that only stores points and tracks, not polygons).