“Our system’s write-to-read latency is approximately 21 h. The majority of this time is taken by synthesis, viz., approximately 305 s per base, or 8.4 h to synthesize a 99-mer payload and 12 h to cleave and deprotect the oligonucleotides at room temperature. After synthesis, preparation takes an additional 30 min, and nanopore reading and online decoding take 6 min.”
Also the amount of data that can be written is very small in general for oligosynthesis. The most high throughout methods are microarrays by Agilent and others (not used in this paper). You can buy about 32 megabits for $6000 (http://www.customarrayinc.com/oligos_main.htm). The actual cost of synthesis is maybe $2000 as a guess.
So currently DNA storage would be good for small datasets that you would like to store for a long time. Physical density is useless most of the time if you can’t efficiently generate a lot of data to begin with.
We would need several orders of magnitude increase in the write capacity, which is slowly being worked on. Typically people would like to compare synthesis costs with Moore’s law, using Carlson curves ( http://www.synthesis.cc/synthesis/2016/03/on_dna_and_transis... ).
However there hasn’t been as much progress in synthesis as in sequencing. Why? My theory is that Theres not a very big market for DNA synthesis, so the big investments needed haven’t really been there. Maybe storage on dna could be that market, but it would need to show quick and easy wins (eg stepping stones of practicality like what early integrated circuits had).