What is the biggest nightmare for high-performance public chains? State explosion.
Every high-TPS chain encounters the same problem: in order to verify transactions, nodes must carry increasingly heavy hardware configurations to store the historical ledger. The end result is that validation rights become more and more centralized, and decentralization gradually becomes just a slogan. Ethereum has tried solutions, such as the EIP-4444 proposal to prune historical data, but what about the data that gets pruned? It can't just disappear.
That's why a dedicated storage layer is needed. When designing new application chains, we adopted a simple yet powerful strategy: only keep the latest state root on the execution layer, and unload all historical block bodies and transaction receipts to Walrus. Through a modular interoperability architecture, we only store Walrus's Blob ID as a pointer on the execution layer—a lightweight index.
The results are clear. The storage pressure on full nodes is greatly reduced, the consensus layer can run faster, historical data is preserved, and auditability is maintained. This is not just an optimization of a component, but a rethinking of the entire system architecture—allowing computation to focus on processing, and storage to focus on storing, each doing its part. Hard drives shouldn't be in the computing center; they should be placed in a dedicated part of the system where they can add value.
Disclaimer: This article is for technical sharing only and does not constitute any investment advice.
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What is the biggest nightmare for high-performance public chains? State explosion.
Every high-TPS chain encounters the same problem: in order to verify transactions, nodes must carry increasingly heavy hardware configurations to store the historical ledger. The end result is that validation rights become more and more centralized, and decentralization gradually becomes just a slogan. Ethereum has tried solutions, such as the EIP-4444 proposal to prune historical data, but what about the data that gets pruned? It can't just disappear.
That's why a dedicated storage layer is needed. When designing new application chains, we adopted a simple yet powerful strategy: only keep the latest state root on the execution layer, and unload all historical block bodies and transaction receipts to Walrus. Through a modular interoperability architecture, we only store Walrus's Blob ID as a pointer on the execution layer—a lightweight index.
The results are clear. The storage pressure on full nodes is greatly reduced, the consensus layer can run faster, historical data is preserved, and auditability is maintained. This is not just an optimization of a component, but a rethinking of the entire system architecture—allowing computation to focus on processing, and storage to focus on storing, each doing its part. Hard drives shouldn't be in the computing center; they should be placed in a dedicated part of the system where they can add value.
Disclaimer: This article is for technical sharing only and does not constitute any investment advice.