In the decentralized storage sector, Arweave has gained attention with its concept of "permanent storage," but it has a critical flaw: once data is on the chain, it is almost impossible to modify. To update information, the only way is to re-upload the entire new dataset, which is not only cumbersome but also generates大量冗余副本, making it completely unsuitable for scenarios like social applications and blockchain games that require frequent updates.

Walrus has solved this problem through technological innovation, enabling real-time and efficient updates of dynamic data.

How is this achieved? The core lies in the "slice-level update" mechanism encoded with RedStuff. Arweave requires a complete retransmission, while Walrus employs a different approach—dividing data into main slices and sub-slices. Users only need to modify the slices corresponding to the changed parts; the entire data does not need to be re-uploaded. When the system receives the updated slices, it quickly reconstructs the new complete data using XOR operations and then synchronizes the updated slices to the storage network. This operation increases update efficiency by dozens of times; tasks that previously took minutes now take only seconds.

In addition to slice updates, Walrus also optimizes the verification process. It integrates with Sui Move contracts to achieve "update and verify" in one step. When users update data, the Move contract automatically verifies permissions to ensure the update is legitimate; simultaneously, it checks the updated slices to guarantee data integrity. This not only improves efficiency but also enhances security.

Compared to Arweave, which emphasizes permanent storage, it appears cumbersome when dealing with dynamic scenarios. Walrus fills this gap by combining distributed storage with on-chain contracts, providing a more optimized storage solution for applications like blockchain games, social platforms, and DeFi that require high-frequency updates.