🎉 Share Your 2025 Year-End Summary & Win $10,000 Sharing Rewards!
Reflect on your year with Gate and share your report on Square for a chance to win $10,000!
👇 How to Join:
1️⃣ Click to check your Year-End Summary: https://www.gate.com/competition/your-year-in-review-2025
2️⃣ After viewing, share it on social media or Gate Square using the "Share" button
3️⃣ Invite friends to like, comment, and share. More interactions, higher chances of winning!
🎁 Generous Prizes:
1️⃣ Daily Lucky Winner: 1 winner per day gets $30 GT, a branded hoodie, and a Gate × Red Bull tumbler
2️⃣ Lucky Share Draw: 10
Gas fees have become a headache for many projects. Every on-chain data update costs money. Especially for high-frequency trading and asset management protocols, maintaining data synchronization alone can incur significant costs.
But recently, some projects have quietly changed their approach. They haven't cut features; instead, they've made calls more flexible and responses faster—while reducing costs at the same time.
The turning point is here: they abandoned the "mindless push" approach and switched to "pull when needed."
Imagine the original oracle model. It's like having a helpful friend who sends you market quotes every minute, whether you need them or not—each message costs you delivery fees. No matter how frequent the updates, you have to accept them all.
Using a data pull mechanism is different. The core logic is: "Don't proactively push; respond passively; appear when needed, stay silent when not."
**In practical terms:**
At the moment a user executes a trade or a contract needs to settle—data is immediately available. Other times? The system remains silent, burning not a single Gas.
High-frequency strategies can pull data at millisecond intervals, while low-frequency scenarios can trigger events as needed. You're no longer bound by continuous data streams but hold the initiative—when to need data, when to call.
**Security remains uncompromised.** Each data pull still requires verification by decentralized nodes, ensuring source traceability and full trustworthiness throughout the process. Cost savings never mean lowering security standards.
The beauty of this approach is that it transforms data costs from fixed expenses into on-demand resource consumption. Already, algorithmic stablecoin projects are using it to optimize minting and redemption processes, and derivatives protocols are employing it for millisecond-level precise calculations.
Their shared realization is—no longer agonizing over "on-chain costs," but learning to "save smartly and use precisely."
When data can truly be as instant and accessible as water and electricity, your protocol design gains cost flexibility. Projects that once saw on-chain data fees as a ceiling are now re-evaluating their architecture.
Think about how much Gas your project spends daily on those "unnecessary" data updates. Share your scenarios in the comments—perhaps "pull on demand" is exactly the breakthrough you're looking for.