I used to lump every “decentralized storage” project into the same bucket. Filecoin, Arweave, whatever new name shows up, it all sounded like the same promise with different branding. But the more I watched how real products behave, the more I realized that bucket is the reason people get confused and bored. “Storage” is not one problem. It’s at least three different problems, and each network solves a different one. Once I started judging them by the problem they solve, Walrus began to make more sense to me, and the comparison became a lot cleaner.
Here’s the simplest way I frame it in my head. If your goal is long-term permanence, you’re thinking like Arweave. If your goal is decentralized capacity and an open market for storage providers, you’re thinking like Filecoin. If your goal is making large data usable inside modern Web3 and AI workflows, you start thinking in the direction Walrus is pushing. These are not “better or worse” versions of the same thing. They are different tools for different jobs, and a lot of arguments online happen only because people don’t define the job first.
Arweave, in my view, is easiest to understand because it’s built around a very clear promise: permanent storage. You put data there with the intention that it stays there and can be referenced forever. That has a specific kind of value. It’s great for archives, public records, historical content, and anything where “never changing” is the point. The trade-off is obvious too. Permanence is not always what applications need. Many real products deal with evolving data. A user updates content. A game changes assets. A dataset gets revised. If your whole model is “store once, keep forever,” you naturally fit some use cases extremely well and other use cases awkwardly.
Filecoin is different. It feels more like a decentralized marketplace for storage. The strength of that model is flexibility and scale through an open network of storage providers. It’s closer to “I want decentralized capacity and incentives for providers to offer it.” That can work well, but it also introduces complexity. Marketplaces come with pricing dynamics, reliability considerations, and sometimes a learning curve for teams trying to integrate it smoothly. The upside is that, at scale, market-driven systems can become powerful. The downside is that not every product team wants to deal with marketplace complexity when all they want is predictable storage they can build on.
Now, where does Walrus fit in this mental model? This is where I think many people frame it wrong, because they hear “storage” and immediately compare it to Filecoin or Arweave on the most basic question: “How cheap is it to store data?” That’s a shallow comparison. What I find more interesting about Walrus is that it looks like it’s being built for active data workloads and data availability, not just the act of storing something somewhere. And that matters because modern applications don’t only store data. They read it constantly, they update it, they serve it to users, and they need to trust that it remains available without relying on one centralized provider.
From a practical standpoint, “data availability” is the problem that shows up when applications scale. It’s the pain of “my app cannot function if this data is not reliably accessible.” That’s different from archiving. That’s different from a pure marketplace for capacity. It’s closer to being a foundational layer for apps that need data to behave like a dependable component of the product. If you build anything media-heavy, AI-adjacent, or user-generated, you eventually hit this wall. You need large blobs to be available, recoverable, and economically sustainable when usage grows.
This is also why the technical design choices matter, but only if we explain them in human terms. When Walrus talks about efficiency and resilience, I don’t treat it as marketing. I treat it as a question of whether the network can keep data available without doing wasteful things like endlessly duplicating full copies everywhere. Systems that rely on heavy replication can become expensive at scale. Systems that use smarter encoding and recovery methods have a better shot at being both resilient and cost-efficient. That’s the difference between a network that works for demos and a network that survives real usage.
The other piece that shapes my view is how these systems fit into developer workflows. Arweave’s permanent storage model is conceptually straightforward, but it’s best for “write once” use cases. Filecoin’s marketplace model can be powerful, but products may face integration overhead and variability they need to manage. Walrus, from what I observe, is trying to feel more like a data layer applications can plug into for ongoing usage, where availability and integration are first-class concerns. If that works, it becomes less of a “storage coin narrative” and more of a real infrastructure component.
Now, if I’m being strict, there’s a risk on Walrus’s side too. Positioning for active data workloads is harder than positioning for archives. You have to prove reliability under real traffic. You have to make retrieval practical. You have to make the developer experience smooth enough that teams don’t abandon the integration halfway. And you have to create a cost structure that teams can plan around. If any of those fail, the thesis stays theoretical. So I’m not writing this like a fanboy. I’m writing it like someone who has watched “good tech” lose because adoption and usability didn’t follow.
This comparison also changes how I think about tokens. People love to argue which token will pump, but that’s not how I evaluate infrastructure. If Arweave is chosen for permanence, demand comes from a specific kind of user behavior: publishing and archiving. If Filecoin is chosen for decentralized capacity, demand comes from storage deals and provider economics. If Walrus is chosen as a data availability layer for active workloads, demand comes from applications that keep using it continuously. Those are different demand profiles. And when you understand the demand profile, you stop expecting every project to behave the same way in the market.
So when someone asks me, “Which one is best?” my honest answer is: best for what. If you need permanent public storage, Arweave makes sense. If you need a decentralized marketplace for storage capacity, Filecoin makes sense. If you need a system designed for frequent access, large blobs, and a future where AI and Web3 apps treat data availability as core infrastructure, then Walrus becomes an interesting candidate. The real mistake is forcing all three into one category and arguing as if they’re competitors in the exact same lane.
My reflection after watching all three narratives for a while is this: most retail attention goes to whatever is easiest to explain in one sentence. Permanence is easy. “Decentralized storage market” is also easy. “Data availability for active workloads” takes more effort to explain, which is exactly why it can be mispriced in the early phase. Whether Walrus earns that role is still an open question, but at least the direction feels aligned with how products are evolving.
Small question to end this: if you had to choose one, do you think the next wave of demand comes from permanent storage, storage marketplaces, or data availability for active AI and Web3 applications?