Product Announcement: Teams in Arraylake
Teams is here for Arraylake paid accounts: group users and API keys, grant roles once, and every member inherits them. Group-level access management for growing data teams.
the data layer for
scientific ai
built for weather & climate|
Cloud-native tensor data management to accelerate problem-solving for our rapidly changing world.
Book a demoTrusted 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.
Why tables fall short for tensor datathe 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.
Learn about open source leadershipsolution overview
Accelerate insights and innovation
Modernize data operations so you can focus on what you do best.
Before (Data Swamp)
With Earthmover
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 How Kettle Uses Earthmover to Power Wildfire Risk Modeling at Scale
How an AI-native insurance company manages 130+ TB of satellite, weather, and geospatial data to model wildfire risk across millions of scenarios.
Learn more
Case Study From GeoTIFF Chaos to Cloud-Native Climate Risk: How Eoliann Built Airis on Earthmover
How Eoliann replaced brittle file-based pipelines with a cloud-native platform to model physical climate risk on critical infrastructure.
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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.
Learn more about our team and missionLatest from the blog
View all posts →Having it all: virtual and materialized data products
A guest post from dynamical.org on how virtual Icechunk Zarrs complement materialized products to deliver low-latency, complete, and fast-access weather data — plus the low-latency NOAA HRRR dataset it describes, now on the Earthmover Data Marketplace.
Virtually Gribberish - Bringing Icechunk clarity to GRIB archives
GRIB data is notoriously hard to work with, so we made it easy to create virtual Icechunk stores from GRIB archives such as the NOAA National Blend of Models, allowing cloud-optimized access to GRIB data archives without copying the data.