accelerate innovation with modern tensor data workflows
Easily operationalize weather, climate, and earth-observation data to predict and prepare for the future.
Talk to an expertMeet your goals faster with modern array-based data management
Save time and money
Save months of development time by adopting the Earthmover managed platform instead of building a bespoke solution — or save on storage, maintenance, and data delivery by streamlining your existing operations.
Collaborate and evolve data safely
Transform scattered data into a single source of truth and empower teams to collaborate in real-time with robust version control and data governance.
Extract more value from your data
Unlock new potential for analysis and product development with cloud-native data management that retains your data's multidimensional structure. Easily operationalize data with a wide array of delivery options.
For organizations turning weather and earth observation data into valuable products and insights
Weather forecasting and AI models
Focus entirely on iterating on model quality instead of data infrastructure or DevOps bottlenecks, even as data sets scale.
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Hedge funds and energy traders
Query weather forecast data like a high-performance database, allowing analysts to easily run backtests and forecasts, enabling faster predictive weather insights that drive alpha.
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Environmental monitoring & risk analysis
Reduce complexity of data product delivery and reduce audit risk with streamlined data workflows and robust data governance.
Government agencies
Fulfill missions by making high-volume public data accessible to public and private scientific communities in a high-performance cloud-native environment.
Scientists and academic institutions
Advance open science by gathering scattered data into a single source of truth on the cloud and enabling collaboration and reproducible experiments.
Arraylake solves all of the challenges I've encountered working with massive weather and climate datasets. It will be my go-to tool for building any new research project or operational project.
Daniel Rothenberg
Atmospheric Scientist
Empower cutting-edge workflows and solutions
Cloud native data loaders for machine learning using Zarr and Xarray
We set up a high-performance PyTorch dataloader using data stored as Zarr in the cloud.
Solving NASA's Cloud Data Dilemma: How Icechunk Revolutionizes Earth Data Access
Earthmover helps NASA achieve 100x performance boost for cloud data analytics with the Icechunk tensor storage engine.