Comparing the speed of multiple json R packages

json-benchmark.R

# R CMD BATCH --vanilla json-benchmark.R
output_dir <- setwd(here::here())
grDevices::dev.set(1)

# simpleBenchmark
file <- system.file("jsonexamples", "twitter.json", package="RcppSimdJson")
jsontxt <- readLines(file)
res <- microbenchmark::microbenchmark(
    jsonify = jsonify::validate_json(jsontxt),
    jsonlite = jsonlite::validate(jsontxt),
    simdjson = RcppSimdJson::validateJSON(file),
    ndjson = ndjson::validate(file),
    RJSONIO = RJSONIO::isValidJSON(file),
    yyjsonr = yyjsonr::validate_json_file(file),
    times = 100L
)
print(res, order="median")
p <- ggplot2::autoplot(res) + ggplot2::labs(title="Validate a JSON file (or string)")
ggplot2::ggsave(here::here(output_dir, "simpleBenchmark.png"), plot = p)


# simpleParseBenchmark
file <- system.file("jsonexamples", "twitter.json", package="RcppSimdJson")
json <- paste(readLines(file), collapse="")
res <- microbenchmark::microbenchmark(jsonify = jsonify::from_json(json),
                                      jsonlite = jsonlite::fromJSON(json),
                                      simdjson = RcppSimdJson::fparse(json),
                                      ndjson = ndjson::flatten(json),
                                      RJSONIO = RJSONIO::fromJSON(json),
                                      yyjsonr = yyjsonr::read_json_str(json),
                                      times = 100L)
print(res, order="median")
p <- ggplot2::autoplot(res) + ggplot2::labs(title="Parsing JSON string")
ggplot2::ggsave(here::here(output_dir, "simpleParseBenchmark.png"), plot = p)

Here my results. I use Ubuntu 22.04.

R version 4.3.2 (2023-10-31) -- "Eye Holes"
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> # R CMD BATCH --vanilla json-benchmark.R
> output_dir <- setwd(here::here())
> grDevices::dev.set(1)
null device 
          1 
> 
> # simpleBenchmark
> file <- system.file("jsonexamples", "twitter.json", package="RcppSimdJson")
> jsontxt <- readLines(file)
> res <- microbenchmark::microbenchmark(
+     jsonify = jsonify::validate_json(jsontxt),
+     jsonlite = jsonlite::validate(jsontxt),
+     simdjson = RcppSimdJson::validateJSON(file),
+     ndjson = ndjson::validate(file),
+     RJSONIO = RJSONIO::isValidJSON(file),
+     yyjsonr = yyjsonr::validate_json_file(file),
+     times = 100L
+ )
Registered S3 method overwritten by 'jsonify':
  method     from    
  print.json jsonlite
> print(res, order="median")
Unit: microseconds
     expr        min          lq        mean      median          uq        max
  yyjsonr    448.825    561.1735    716.8716    667.8380    759.3715   3354.802
 simdjson    445.594    587.3300    836.7611    774.2215    918.8510   6301.559
  jsonify   3702.561   4241.7280   5074.4840   4676.2690   5337.2575  11296.512
 jsonlite   6819.402   7553.0285   9101.7492   8517.3535   9302.2035  23988.623
  RJSONIO  13915.231  15173.1345  17323.3559  17300.2420  17937.9050  31750.315
   ndjson 132535.668 147297.1685 167922.0323 158292.6110 166997.3670 290134.665
 neval  cld
   100  b  
   100  b  
   100 ab  
   100 a   
   100    d
   100   c 
> p <- ggplot2::autoplot(res) + ggplot2::labs(title="Validate a JSON file (or string)")
> ggplot2::ggsave(here::here(output_dir, "simpleBenchmark.png"), plot = p)
Saving 7 x 7 in image
> 
> 
> # simpleParseBenchmark
> file <- system.file("jsonexamples", "twitter.json", package="RcppSimdJson")
> json <- paste(readLines(file), collapse="")
> res <- microbenchmark::microbenchmark(jsonify = jsonify::from_json(json),
+                                       jsonlite = jsonlite::fromJSON(json),
+                                       simdjson = RcppSimdJson::fparse(json),
+                                       ndjson = ndjson::flatten(json),
+                                       RJSONIO = RJSONIO::fromJSON(json),
+                                       yyjsonr = yyjsonr::read_json_str(json),
+                                       times = 100L)
> print(res, order="median")
Unit: milliseconds
     expr       min        lq      mean    median        uq        max neval
  yyjsonr  2.752954  2.957143  3.651587  3.194147  3.721455  20.270499   100
 simdjson  3.633885  4.161745  4.978973  4.577095  5.280067   9.053087   100
  jsonify 14.386760 15.592567 19.508955 17.084299 22.976594  31.150945   100
  RJSONIO 18.121915 20.266469 24.436466 22.608387 26.761010  42.650437   100
   ndjson 45.317341 49.499249 58.937256 53.639392 60.690322 129.146639   100
 jsonlite 46.134665 53.321075 61.141952 56.703371 62.757238 107.240635   100
  cld
   c 
   c 
 a   
    d
  b  
  b  
> p <- ggplot2::autoplot(res) + ggplot2::labs(title="Parsing JSON string")
> ggplot2::ggsave(here::here(output_dir, "simpleParseBenchmark.png"), plot = p)
Saving 7 x 7 in image
> 
> proc.time()
   user  system elapsed 
 42.560   1.587  42.544