In the Web3 storage sector, project teams always love to showcase a bunch of technical parameters—who has the lowest redundancy, who has the highest throughput, who can recover data the fastest. But when you really shift your focus from whitepapers to real-world applications, you'll hit a sobering fact: optimal parameters do not necessarily equal commercial success.

I've been observing the evolution of storage protocols for a long time, from Filecoin's "mining economics" to Arweave's "permanent storage" IP, and various high-end erasure coding schemes. I've seen too many projects with dazzling technical metrics that no one actually uses. In comparison, RedStuff's 2D erasure coding approach is somewhat unconventional—redundancy only needs to be 4-5 times (some competitors boast below 3 times). Although recovery speed has improved significantly, it doesn't aim for millisecond-level extremes.

This kind of "restraint" is actually very clever.

Here's the data: a leading storage protocol's 25x redundancy scheme, storing 100GB of data costs thousands of dollars per year, and data recovery can take several hours. While permanent storage schemes emphasize immortality, their costs and access latency are equally daunting. RedStuff, through targeted optimization, reduces costs by over 80%—annual storage fees are controlled around $2,400, and recovery time is cut to 36 minutes.

What's even more interesting is that it doesn't aim to be all-encompassing. It precisely targets two scenarios: one is AI training data (cost-sensitive + high-frequency access), and the other is RWA asset credentials (long-term storage + compliance requirements). Instead of overextending into areas they’re not good at, they focus on excelling in their target scenarios—this is the practical approach.

Technology shouldn't be a game of competing parameters, but rather about truly solving pain points in business. From this perspective, the emergence of such projects may be changing the competitive logic of the storage sector.