Futures
Access hundreds of perpetual contracts
TradFi
Gold
One platform for global traditional assets
Options
Hot
Trade European-style vanilla options
Unified Account
Maximize your capital efficiency
Demo Trading
Introduction to Futures Trading
Learn the basics of futures trading
Futures Events
Join events to earn rewards
Demo Trading
Use virtual funds to practice risk-free trading
Launch
CandyDrop
Collect candies to earn airdrops
Launchpool
Quick staking, earn potential new tokens
HODLer Airdrop
Hold GT and get massive airdrops for free
Launchpad
Be early to the next big token project
Alpha Points
Trade on-chain assets and earn airdrops
Futures Points
Earn futures points and claim airdrop rewards
Ladies and gentlemen, today let's talk about something practical—have you ever wondered how much of the money you pay to cloud storage providers each year is actually valuable, and how much is just wasted? Recently, I took a deep dive into a project called Walrus Protocol. This thing is quite ambitious, aiming to fundamentally change the pricing structure of the storage market. What's its secret weapon? Decentralization +全民参与 (全民参与 means "mass participation"), giving everyone the opportunity to become a storage provider.
Let's start with the technically hardcore part. This protocol uses the Red Stuff algorithm, which is indeed quite impressive. Do you know that traditional decentralized storage solutions (like a well-known scheme) usually replicate data more than ten times to ensure data security? That's a huge waste. Walrus only needs 4 to 5 copies to achieve the same level of reliability. What's the secret? They store files by splitting them into "Lego blocks," so even if some data is lost, it can be fully restored through mathematical algorithms. Just looking at the testnet data is quite shocking—storing a large 1TB file can save over 60% of Gas fees compared to traditional schemes. This is a real boon for Web3 developers because those fuel costs can really drive you crazy.
But saving costs alone isn't enough; it also has to be user-friendly. I tried their Quilt upload tool, especially for scenarios involving massive numbers of small files—for example, a million images needed for AI model training. Uploading them one by one using traditional methods? That would take forever. Quilt uses batch upload, which is about three times faster, significantly improving efficiency. There's also a thoughtful detail: you can customize storage strategies, such as prioritizing European nodes for European users' data (to comply with GDPR), or storing Asian users' data in Asia (to reduce access latency). This flexibility and localization capability is something that some large companies need to open a bunch of support tickets to handle, but they can do it directly through configuration.
The ecosystem construction is also steadily progressing. Through deep cooperation with the Sui public chain, Walrus is gradually expanding its application scenarios within that ecosystem, and there’s still plenty of room for imagination.