Blockchain is like a massive database that charges based on computation frequency, while traditional DApp development is akin to building a warehouse in this database without a shopping guide—users have to pay high fees every time they query or write data. In the highly competitive Web3 ecosystem of 2025, these costs are becoming increasingly unsustainable.

Recently, I encountered a similar issue while optimizing a decentralized trading protocol based on Ethereum L2. On the surface, it appeared to be standard contract operations, but internally, the looping reads had become the main reason for draining user funds. By introducing asynchronous data fetching mechanisms and off-chain index preprocessing, I reduced the gas cost per interaction from around 0.012 ETH to approximately 0.004 ETH—a significant improvement.

The key is that this optimization was not achieved by removing features or reducing security but by rethinking the storage architecture of the blockchain.

The most expensive operations on a blockchain are always real-time computation and storage synchronization. In traditional Solidity development, we are accustomed to directly accessing data via mappings or arrays during contract execution. This was standard practice in the past, but in the multi-layered structure after Ethereum's Pectra upgrade, it is highly inefficient. The core idea of data fetching is simple: shift the process of locating data from the costly on-chain computation layer to a much cheaper off-chain index or computation layer.

This approach may seem simple, but it actually represents a new understanding of L2 scaling and on-chain cost optimization. In the future, such off-chain preprocessing solutions will become increasingly important.