library("microbenchmark")
library("ggplot2")
library("RSocrata")
set.seed(5125)

A smaller dataset

# https://github.com/hadley/dplyr/issues/1162#issuecomment-137870577
small <- microbenchmark(
  read.socrataRBIND("https://soda.demo.socrata.com/resource/4334-bgaj.csv"),
  read.socrataPLYR("https://soda.demo.socrata.com/resource/4334-bgaj.csv"),
  # read.socrataDPLYR("https://soda.demo.socrata.com/resource/4334-bgaj.csv"), will not work due to stricktness
  read.socrataDATATABLE("https://soda.demo.socrata.com/resource/4334-bgaj.csv"),
  times = 3L,
  unit = "s"
)

small
## Unit: seconds
##                                                                           expr
##      read.socrataRBIND("https://soda.demo.socrata.com/resource/4334-bgaj.csv")
##       read.socrataPLYR("https://soda.demo.socrata.com/resource/4334-bgaj.csv")
##  read.socrataDATATABLE("https://soda.demo.socrata.com/resource/4334-bgaj.csv")
##       min       lq     mean   median       uq      max neval cld
##  2.191054 2.241334 2.576792 2.291613 2.769661 3.247710     3   a
##  2.024973 2.160264 2.246209 2.295555 2.356828 2.418101     3   a
##  2.050385 2.052602 2.183463 2.054818 2.250002 2.445186     3   a
boxplot(small)

A large one

# 5878399 rows
# https://data.cityofchicago.org/resource/6zsd-86xi.csv
# 49142
# https://data.ny.gov/resource/hrvs-fxs2.csv
# 618029
# https://data.ny.gov/resource/cwsm-2ns3.json
bigger <- microbenchmark(
  read.socrataRBIND("https://data.ny.gov/resource/cwsm-2ns3.csv"),
  read.socrataPLYR("https://data.ny.gov/resource/cwsm-2ns3.csv"),
  read.socrataDPLYR("https://data.ny.gov/resource/cwsm-2ns3.csv"), # will not work due to stricktness
  read.socrataDATATABLE("https://data.ny.gov/resource/cwsm-2ns3.csv"),
  times = 3L,
  unit = "s"
)

bigger
## Unit: seconds
##                                                                 expr
##      read.socrataRBIND("https://data.ny.gov/resource/cwsm-2ns3.csv")
##       read.socrataPLYR("https://data.ny.gov/resource/cwsm-2ns3.csv")
##      read.socrataDPLYR("https://data.ny.gov/resource/cwsm-2ns3.csv")
##  read.socrataDATATABLE("https://data.ny.gov/resource/cwsm-2ns3.csv")
##       min       lq      mean   median        uq       max neval cld
##  68.38030 73.93804  77.45024 79.49577  81.98521  84.47465     3   a
##  71.67357 73.74924  74.87746 75.82491  76.47941  77.13390     3   a
##  69.47432 70.23169 107.55303 70.98906 126.59239 182.19571     3   a
##  64.93302 66.28510  67.44425 67.63717  68.69986  69.76254     3   a
boxplot(bigger)