The real challenge of decentralized storage is right in front of us: how to ensure high fault tolerance without letting costs spiral out of control?

The Walrus protocol provides an answer with its self-developed RedStuff 2D encoding technology. Compared to traditional solutions, its approach is entirely different. Filecoin uses Reed-Solomon encoding, Arweave adopts a full network replication model, while Walrus chooses a 2D encoding strategy, breaking through the storage efficiency ceiling.

Let's take a look at how it works. The core of RedStuff lies in the "hierarchical encoding of primary and secondary dimensions" logic. The primary dimension uses an f+1 recovery threshold, which can be achieved with just 3x replication factor for asynchronous writing; the secondary dimension expands through 2D encoding, adding only 1.5x redundancy, ultimately keeping the total replication factor at 4-5x. What does this mean? Filecoin requires 25x redundancy, Arweave is at the hundredfold level, and Walrus directly cuts this number down, making its advantage clear.

Performance-wise, there’s no compromise. Replacing complex polynomial calculations with simple XOR operations, encoding and decoding speeds are tripled. Restoring 1TB of data doesn’t require all shards—only a subset—so even if two-thirds of the nodes in the network go offline, data can still be reconstructed completely. This fault tolerance is especially practical in production environments.

Cost reduction is the most straightforward metric. The annual storage cost for 1TB drops to $50, saving 80%-98% compared to traditional solutions. At the same time, data availability remains stable at 99.9%, with retrieval latency ≤500ms, making it particularly suitable for scenarios with high-frequency access to hot data.

RedStuff also solves another difficult problem in storage proofs—scalability. Proof costs grow logarithmically with the number of files, allowing the network to scale horizontally to thousands of nodes, which is critical for large-scale applications. As a technological reserve of Mysten Labs, this encoding scheme has already been tested in the Sui mainnet, providing efficient solutions for high-frequency storage needs such as AI datasets and L2 transaction data.