Recently, I’ve read quite a few discussions about the storage track, with everyone debating who is cheaper and whose data lasts longer. Of course, these are important, but this way of thinking is a bit like a landlord who only knows how to expand warehouse space and is indifferent to the flow of goods — completely missing the point.

What can truly trigger large-scale applications are not cold, backup files. Projects like games, social networks, and dynamic NFTs deal with living, hot data — data that needs to be read, modified, and combined quickly at any time. Currently, many on-chain storage solutions fall short: they are either slower than a snail or the cost of modifications is outrageously high.

That’s why I get excited when I see certain storage protocols. They’re not just researching “how to store cheaper,” but understanding “how to use it more smoothly.” The development team behind them comes from a background in low-level high-performance architecture, directly applying ideas from high-performance public blockchains’ object storage and parallel processing. What does this mean? For example, in blockchain games, your equipment attributes and character skins are no longer scattered into a bunch of small files but are integrated into a single object that can be read quickly and updated uniformly. You only feel the game is smooth and seamless, unaware that behind the scenes, there’s a qualitative leap in data architecture.

Another detail — they use erasure coding technology. This tech isn’t new; other projects are also using it, but this team has made a key innovation: they don’t just see it as a redundancy backup solution but combine it with the real-time data access needs of hot data. Simply put, when you need to fetch data, the system can simultaneously retrieve data fragments from multiple nodes in parallel, and the speed of stitching them together is faster than pulling the entire data from a single source. It’s like shopping at a market, buying different vegetables from several stalls at once, and finally putting them into a basket — saving time compared to queuing at one stall to get everything you need.

This approach is fundamentally not about “who has the cheapest storage,” but about “whether it can support real-time on-chain applications.” From this perspective, the second half of the storage track’s competition may really shift from “storage capacity and price” to “data architecture and access efficiency.”