The open source core for scientific data
Adopt the open source standard for organizing and collaborating on array data in the cloud.
The Python stack for scientific data
Earthmover founders Dr. Ryan Abernathey and Dr. Joe Hamman, have spent their careers doing cutting-edge research in climate science, remote sensing, and cloud-native data analytics. They maintain numerous critical open-source scientific Python packages, including Xarray, Zarr, and the Pangeo Project, used by leading institutions and scientific researchers and by teams at the forefront of AI modeling for Earth-system simulation.
Trusted by leading institutions and ground-breaking innovators
Maintain the rich context of tensor data with Xarray
Earthmover helps maintain Xarray, the leading Python package for working with labeled multidimensional array data.
The Earthmover platform integrates with Xarray and adds a user-friendly data catalog to unify data organization and facilitate data discovery.
Flexible, performant storage and access with Zarr
The Zarr data format and Python library enables efficient storage and fast data access with chunked, compressed storage for multidimensional arrays. The Earthmover team helps maintain Zarr and recently announced Zarr 3.
The Earthmover platform extends Zarr’s efficient data access by empowering applications and users to query data fast at any scale via WMS, OCG EDR, or OpenDAP.
Evolve data safely with Icechunk
The Earthmover team created and open-sourced Icechunk, a transaction storage engine for Zarr data to handle the version control and seamless updating needs of geospatial and weather data workflows. Icechunk delivers 10x performance improvements over other cloud storage libraries.
The Earthmover platform harnesses the performance of Icechunk and adds data governance and usage monitoring to help teams reduce costs, maintenance, and risk.
Pangeo Project
The Pangeo Project is a community for open, reproducible, scalable geoscience supported by NASA and the National Science Foundation. As key contributors within this community, we are defining the reference architecture for cloud-native multidimensional data to accelerate collaboration and reproducible open science.
Build smarter with expert guidance
Accelerate your roadmap with expert guidance from climate scientists and data engineers building the leading open source solutions and defining the modern workflow for multidimensional data.