Analyzing a Web3 project, many people tend to fall into the trap of a single-dimensional perspective. My approach is to directly compare it with other solutions side by side, which actually helps reveal its essence—what problem it truly aims to solve, what trade-offs it makes, and which track it is most likely to succeed in.

I roughly categorize the storage solutions on the market into three different styles:

**First: Centralized Cloud Storage**

The advantages are obvious—easy to use, fast response, low cost, mature interface systems. But what’s the cost? Trust is fully placed on a single company. Data can be deleted or modified at will; you simply cannot embed the attribute of "content trustworthiness" into on-chain logic. Many Web3 projects use this solution as a quick way to launch, but in the long run, this is not "truth recognized by the chain." Being usable does not mean being stable.

**Second: Traditional Decentralized Storage**

Resistant to censorship, distributed, harder to cut off than centralized solutions—sounds perfect. But in reality? Many solutions are more like "distributed cloud drives." Storage issues are solved, but for on-chain applications, details like data referencing, verification, access control, and lifecycle management often need to be handled by developers themselves. You can use it, but often with manual debugging. That’s why project teams love to shout "We are fully decentralized," while developers complain "This stuff is too much of a hassle."

**Third: Chain/Ecosystem Native Data Layer**

This type of solution focuses on a different aspect—prioritizing how data can be directly referenced by on-chain applications, how to implement verifiability, and how to deeply couple with contract logic. It doesn’t aim for perfection in every aspect, but strives to be the most seamless in on-chain application scenarios.

To truly understand the value of a storage solution, the key question is: what choices does it make across these three dimensions? Where are the compromises?