It leads people to believe this will be a compression improvement for all their content, but after they do the work to integrate it they may discover that it's only a slight improvement because their content isn't identical to the content its static dictionary was designed for.
It's at least a very good codec, though, so it's still a win for other data. Just smaller than you might expect.
Also note that the dictionary is strongly biased towards English. Sure, there is some Russian, Chinese, Arabic (and probably some other scripts in there which I don't recognize), but there seems to be more English words in there than all those others combined. If you're compressing small documents in any other language than English, it might not be worth it to use Brotli.
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Unlike other algorithms compared here, brotli includes a static dictionary. It contains 13’504 words or syllables of English, Spanish, Chinese, Hindi, Russian and Arabic, as well as common phrases used in machine readable languages, particularly HTML and JavaScript. The total size of the static dictionary is 122’784 bytes. The static dictionary is extended by a mechanism of transforms that slightly change the words in the dictionary. A total of 1’633’984 sequences, although not all of them unique, can be constructed by using the 121 transforms. To reduce the amount of bias the static dictionary gives to the results, we used a multilingual web corpus of 93 different languages where only 122 of the 1285 documents (9.5 %) are in languages supported by our static dictionary.
It isn't a static dictionary; it just has a (large) initial value, unlike gzip.
Brotli is a great compressor, especially at levels 2-5. Unfortunately, the Google paper on Brotli runs tests at levels 1 and 11. I don't get that at all when their stated goal was to replace gzip.
It's at least a very good codec, though, so it's still a win for other data. Just smaller than you might expect.