the cloud platform for

Modern data operations for data cubes to accelerate problem-solving for our rapidly changing world

Trusted by leading institutions and ground-breaking innovators

Data cubes pose unique challenges

Conventional data platforms struggle with multidimensional array data. Teams often build custom solutions, wasting months of development time.


Earthmover provides a better approach to array data management.


the earthmover platform

Finally, a platform purpose-built for tensor data

Deliver powerful and scalable data products, streamline operations, and reduce storage and maintenance costs 

cloud-native

Industry-leading performance for data science and AI

Earthmover’s cloud native data architecture eliminates I/O bottlenecks and accelerates data-intensive applications.

collaboration

Central source of truth for fast-paced collaboration

Find, share, update, and audit your tensor data assets all in one place. Experiment and prototype quickly and safely with git-style data version control.

data delivery

Scalable APIs for rapid data and product delivery

Remove bottlenecks from data exploration and product delivery with scalable APIs for querying large array datasets via OGC EDR, OpenDAP, WMS – or direct Xarray interaction. 

Built by the leaders behind the open source standard for scientific data

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. The team maintains critical open-source scientific Python packages, including Xarray, Zarr, and the Pangeo Project, used by teams at NVIDIA, NOAA, Google, Microsoft, and more.

solution overview

Accelerate insights and innovation

Modernize data operations so you can focus on what you do best.

01

Unify data and governance

Centralize data access, data cataloging, and git-style version control, so teams can collaborate in real-time and maintain data provenance. Simplify data pipelines, reduce code complexity, and avoid DevOps bottlenecks, even as datasets scale. 

02

Optimize I/O performance for AI/ML and Data Science

Most data science workloads are I/O bound. Accelerate model training, analytics, and decision making as you scale with a universal cloud-native tensor storage engine. 

03

Production-ready data delivery

Explore and analyze datasets with your preferred tools. Easily operationalize and distribute datasets and data products with scalable, standards-compliant APIs. 

case studies

Empower cutting-edge workflows

and solutions

Learn how customers use Earthmover to modernize data workflows for weather forecasting, climate modeling, environmental monitoring and more.

Case Study

Scaling Carbon Market Intelligence: Sylvera's Path to Data Efficiency

Scaling Carbon Market Intelligence: Sylvera's Path to Data Efficiency

How a leading carbon ratings provider eliminated data bottlenecks with Arraylake's cloud-native geospatial platform

Case Study

ALIVE at The University of Wisconsin-Madison

ALIVE at The University of Wisconsin-Madison

The University of Wisconsin-Madison is home to a research team called Advanced Baseline Imager Live Imaging of Vegetated Ecosystems (ALIVE).

Advancing problem solving for humanity’s biggest challenges
about earthmover

Advancing problem solving for humanity’s biggest challenges

At Earthmover, we envision a world in which scientific data can be explored, visualized, analyzed, shared, and built upon effortlessly. We are providing a foundation for people and organizations to create new scientific knowledge and data-driven products which will help humans thrive in sustainable harmony with each other and with our planet. 


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