Codecs
Learned codecs against zstd, SZ and ZFP
We ran the same ten datasets through general-purpose, scientific and learned compressors. Where neural codecs win, and where they don’t.
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Keep reading
- Scientific data
What an error bound actually guarantees
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- Case studies
Shrinking a national climate archive
· 12-page PDF
- News
GRIB2 and Zarr v3 support in the Compress SDK
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- Storage & cost
The real cost of keeping a petabyte
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Research partnership on compressing climate model output
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- News
Flowershift launches Compress
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See it on your own data.
Every demo is run by the people who build Compress, on a sample of your own files.