The Data Dilemma in Web 3
Web 3 has succeeded in decentralizing value and logic,
but the data itself is still often centralized or expensive to store.
The problematic question:
How can decentralized assets (NFTs, AI, dApps) rely on a storage architecture that is prone to failure or censorship?
The traditional approach
Most decentralized storage solutions rely on multiple copies to ensure availability,
which is an effective solution but economically inefficient with big data.
Walrus Approach
Walrus provides a different model through Erasure Coding:
Dividing data into encoded chunks
Rebuilding it even with the loss of the majority of nodes
Higher efficiency and lower cost
Then it adds a more important dimension through Sui:
Data is not just stored… but programmable.
Conclusion
The real transformation is not in where we store the data,
but in how we make it:
Decentralized
Robust
And programmatically interactive
Walrus does not just solve the storage problem, but redefines it.
#walrus $WAL