Storage is a topic that has been widely discussed in the Web3 community, with keywords always revolving around cost, speed, and decentralization. These are indeed important, but they are only surface-level issues — what truly determines how far an infrastructure can go is whether the ecological network effect can take hold.

The interesting part about Walrus is right here. It’s not just about stacking hardware or optimizing algorithms, but about using data to build a "gravitational field" for the entire ecosystem.

Imagine this scenario: an application stores data, which not only saves costs but more importantly connects to a standardized, interoperable data network. When hundreds of applications (now over 360) do this, something magical happens — data language becomes unified. New developers don’t need to build storage architectures from scratch; datasets verified by neighboring DeFi protocols are readily accessible; asset metadata from a game can be directly referenced by NFT projects. This significantly reduces innovation costs, and the entire ecosystem’s iteration speed accelerates.

This effect is compounded. Looking at on-chain data, the total storage on the Walrus network has already surpassed 1.3PB, with over 22 million calls daily. Every byte stored and every cross-application call is strengthening the moat of the data network. The cost of application migration will increase exponentially over time because data dependencies within the ecosystem are becoming deeper.

Its barrier isn’t technological patents but ecosystem consensus and the accumulated data relationships — this is something more difficult to replicate than any short-term marketing. This is the true competitive advantage of infrastructure.