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❄️ Snowflake and the Separation of Storage from Compute

A 3D shared storage layer of micro-partitions with independently scalable virtual warehouses querying it above — resize, spin up, prune and auto-suspend compute without moving the data.

AI & Machine Learning3DAdvanced60 FPS

A shared, micro-partitioned storage layer sits below independent virtual warehouses that query it above — resize compute, add or suspend warehouses, and watch billing and query behaviour respond without the data ever moving.

🔬 What It Demonstrates

Storage (the disc of micro-partitions) and compute (the floating warehouse platforms) are decoupled: multiple warehouses can read the same partitions concurrently, each scaling and billing independently of the data layer beneath it.

🎮 How to Use

Add active warehouses, change their size, and dial up query load. Toggle clustering-key pruning to compare a targeted scan against a brute-force full scan, and toggle auto-suspend to see idle warehouses shrink and stop billing credits.

💡 Did You Know?

Because compute is elastic and separate from storage, Snowflake warehouses can resize or suspend in seconds — you pay per-second for compute you actually use, while storage is billed separately and far more cheaply.

⚙ Under the hood

A 3D shared storage layer of micro-partitions with independently scalable virtual warehouses querying it above — resize, spin up, prune and auto-suspend compute without moving the data.

machine learningdata sciencevirtual warehousesscalable computingstorage optimizationcloud computingThree.js

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install