Storage Reduction
60%
On geospatial data
Compression
Lossless
Bit-for-bit reconstruction
ERA5 Zarr
37%
Better than Zstd
Formats
6+
GRIB, NetCDF, COG…
Random Access
Chunk-level
No full-file reads

Geospatial & Scientific Data Products

Purpose-built compression for EO, weather, and raster workflows

Get Started in Minutes

Install the Byte2Bit Atlas SDK or GDAL plugin and start compressing geospatial data immediately. Works as a drop-in layer in GDAL, QGIS, Rasterio, and Python pipelines with no workflow changes needed.

GRIB2NetCDFZarrHDF5Cloud-Optimized GeoTIFFNumPyLiDAR (LAS/LAZ)
terminal
# Install Byte2Bit Atlas
$ pip install byte2bit-atlas
# Compress a NOAA GFS forecast
>>> import byte2bitZarr as b2b
>>> b2b.transform('gfs_0p25.grib2', 'gfs_0p25.b2b')
>>> b2b.verify('gfs_0p25.grib2', 'gfs_0p25.b2b')
✓ Lossless verification passed
✓ 52% storage reduction (2.50 GB → 1.19 GB)
✓ Random-access read: 8 ms per chunk

Customer Feedback

"

We tested Byte2Bit's lossless compression on raw global weather data across multiple variables, benchmarking against zlib and other open-source alternatives. Byte2Bit achieved up to 20% better compression ratios while improving decompression performance significantly. Based on our results, it outperforms any open-source solution we are aware of, offering a superior combination of storage reduction and efficient data retrieval for large-scale scientific datasets.

Lukas Hedegaard Morsing

Machine Learning Scientist, InCommodities

Tested on DMI/NOAA datasetsERA5 Zarr benchmarkedDAS sensor data verified

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