Walrus didn’t try to “optimize” existing storage designs.
It replaced the core idea behind them.
At the heart of Walrus is Red Stuff — a new erasure coding protocol built specifically for decentralized, adversarial, and asynchronous networks.
Traditional storage systems encode data in one dimension. This works until something goes wrong. When nodes churn or go offline, recovery becomes expensive, slow, and network-wide. Over time, these systems lose the very efficiency they promised.
Red Stuff takes a different approach: two-dimensional encoding.
Instead of storing one encoded slice per node, Walrus stores two correlated slivers per node—one in each dimension. This simple shift unlocks a powerful property:
self-healing storage.
When a node loses data or joins late, it doesn’t need the full file to recover. It only needs a small fraction of symbols from other nodes. Recovery bandwidth scales with the lost data, not the size of the blob itself. That’s the difference between fragile efficiency and sustainable scalability.
But Red Stuff does something even more important.
It allows Walrus to support storage challenges in fully asynchronous networks—something no prior protocol could safely do. Attackers can delay messages. They can try to game timing. Red Stuff makes those tricks useless by separating read thresholds from recovery thresholds.
The result?
Strong security with only ~4.5× replication
Efficient recovery even under heavy churn
Verifiable storage without relying on network timing assumptions
This is why Walrus doesn’t just store data efficiently—it stays efficient over time.
In the next post, we’ll break down why asynchronous storage challenges matter and how Walrus prevents nodes from pretending to store data they don’t.
