How Caching with Vercel Solves RPC Bottlenecks for dApps
Why dApp Developers Struggle: The RPC Problem
RPC bottlenecks are the silent killer of dApp performance and scalability. Every dashboard, swap, or balance fetch hits remote blockchain nodes—slow, expensive, and impossible to scale without help. As your user base grows, so does your infrastructure cost and the risk of poor UX.
Polling: The Hidden Drain on Performance and Cost
Most web3 frontend libraries simulate "real-time" by polling. What seems like a live event listener is often just a repeated RPC call under the hood—every few seconds, for every contract watched.
Example: Libraries like Thirdweb, ethers.js, and web3.js often poll every 5 seconds per active listener. Watching 10 contracts? That's 120 RPC calls per minute per user—even if nothing changed.
- Polling is subtle but expensive. Even when using hooks like useEventListener, unless you explicitly use a WebSocket provider, polling is the default.
- On busy dashboards, polling is often the largest driver of total RPC calls and costs.
- Polling can trigger API rate limits, inflate your cloud bills, and slow down your site during traffic spikes.
Alternatives to Polling: Event-Driven Listening
- WebSockets: Use event subscriptions that push updates only when something changes. Some providers and SDKs (ethers.js with WebSocket, custom relays) support this and can broadcast updates app-wide.
- Webhooks (e.g., Thirdweb Engine): For backend event-driven architectures, receive push notifications for contract or transaction changes—no polling, no redundant traffic.
- Custom Shared Connections: In React or similar, build hooks that maintain a single WebSocket per session and only update UI when real changes are detected.
Comparison: Polling vs. Event-Driven Updates

The RPC Problem in Numbers
- Latency: RPC endpoints are much slower than Web2 APIs, especially under congestion.

- Web2 APIs are typically 3–20x faster than blockchain RPC endpoints. Under stress, blockchain queries can be 100x+ slower.
- Cost: Providers like Infura and Alchemy charge per RPC call, and "free" tiers vanish fast at scale.
- Limits: Rate limits and timeouts threaten reliability.
- UX impact: Even a single wallet dashboard can rack up dozens of RPC calls per page. At scale, your traffic (and cost) explodes.
Real Example
- Read: A dashboard showing ETH price, user balance, and index composition can trigger 3–10+ RPC calls per page load.
- Write: Every mint, swap, or vote is another batch of RPC calls—multiply this by hundreds or thousands of users.
Relievement with Vercel: Turning RPC Bottlenecks into Fast User Experiences
What if you could cache these expensive blockchain queries, so users get instant, consistent results—and your backend costs drop dramatically?
Vercel’s caching infrastructure makes it possible to intercept, cache, and optimize all your dApp’s blockchain data, at every layer:
The Three Key Caching Layers
Server layer
- Your backend logic (API routes, endpoints) fetches blockchain data and sets cache headers for downstream layers.
CDN Layer (Edge Network)
- Vercel’s global CDN caches your API/page responses and serves them instantly to users worldwide. Most RPC calls only need to happen once per cache window!
Browser Layer
- End-user browsers cache semi-static data for even faster repeat access.
Visual Flowchart: Blockchain Data Caching
- User → Browser → CDN → Server (where RPC calls happen)
- Each hop is a caching opportunity. Most RPC calls should hit the server only once per cache window.
Practical Example: Caching Blockchain Reads
Say you want to show the latest ETH price from an on-chain oracle.
Without caching: Every user triggers a fresh RPC call on every page load.
With Vercel caching: The first user in each region triggers the RPC call. All other users get a cached result from the CDN—slashing RPC traffic and cost.

Result: 10,000 users? Still just 1 RPC call per minute, per region.
Caching Strategies for Write Transactions
When Not to Cache
- User-specific data (balances, positions) should not be cached globally; use private, no-store.
- On-chain write actions (mint, swap, approve) should go direct; never cache transaction endpoints!
Smart Cache Invalidation
- After a transaction, use On-Demand ISR to force-refresh cached endpoints.
- Keep your app fresh without constant polling.
FAQ: Caching and Blockchain RPC
Q: Does caching hide real-time blockchain changes?
A: For dashboards and analytics, caching for seconds or minutes is a worthwhile trade-off. For true real-time, pair with WebSockets/webhooks for instant events.
Q: How do I cache user dashboard data?
A: Use browser or per-wallet caching—never share private info between users. Use private cache headers.
Q: What about analytics?
A: Aggregate and cache on-chain data in your backend for fast, scalable insights.
Looking Ahead: Leverage Vercel AI for Web3 Teams
The Vercel v0 AI model (v0-1.0-md) was officially released in May 2025 and is currently in beta. Purpose-built for modern front-end and web3 development, v0 supercharges productivity in dApp and infra teams:
- Generate and autofix cache logic with AI-powered code suggestions.
- Explain cache headers for devs and non-devs alike.
- Recommend optimal caching patterns for your web3 use case.
- Streaming responses: Receive real-time code completions and fixes.
- Multimodal input: Accepts both text and image input for a flexible dev experience.
Bonus: v0 is compatible with Cursor and other OpenAI-compatible tools, enabling AI-driven PR reviews, onboarding, and codebase improvement at scale.
Conclusion
Scaling a dApp means solving the RPC challenge at its root.
- Cut infrastructure costs and API bills.
- Boost reliability—even during mainnet congestion.
- Free up your team to focus on features, not plumbing.
Vercel’s caching + modern web3 patterns = the foundation for the next generation of crypto apps. For a caching audit or to discuss scaling your dApp, contact our experts today.