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Hyperliquid Trading Dashboard

A dashboard for real-time whale trades, liquidations, and trending tokens from Hyperliquid using Quicknode's Hypercore gRPC.

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Frontend Framework/Library:
Next.js
Language:
TypeScript
Build Tool/Development Server:
npm
Sample app preview

Overview

This sample app streams every trade from Hyperliquid via Quicknode's Hypercore gRPC and filters for whale trades, liquidations, and trending tokens. gRPC bidirectional streaming delivers data with sub-second latency, with no polling required.


Additional Resources

For video walkthrough of building the app, check out our video

Architecture​

      Quicknode Hypercore gRPC
        (stream every trade)
                  │
                  ▼
        ┌─────────────────┐
        │     Worker      │
        │  Filter + Agg   │
        └────────┬────────┘
                 │
    ┌────────────┼────────────┐
    ▼            ▼            ▼
 Whales    Liquidations   Trending
 (≥$50K)                  (1m buckets)
    │            │            │
    └────────────┼────────────┘
                 ▼
        ┌─────────────────┐
        │    PostgreSQL   │
        └────────┬────────┘
                 │
                 ▼
        ┌─────────────────┐
        │     Next.js     │
        │  [15m/30m/1h]   │
        └────────┬────────┘
                 │
                 ▼
        ┌─────────────────┐
        │    Dashboard    │
        └─────────────────┘

Features​


  • Whale trade detection (≥$50K notional, configurable)
  • Liquidation tracking with full metadata (user, mark price, method)
  • Trending tokens ranked by trade count with buy/sell breakdown
  • Time window filtering (15m, 30m, 1h)
  • Custom coin tracking, any Hyperliquid token
  • Volume sparklines with trend indicators
  • Explorer deep links for trade verification
  • 1-minute aggregation buckets for efficient trending queries

Prerequisites​


  • Node.js 20+ installed
  • A PostgreSQL instance, you can use a platform like Aiven to spin up a hosted instance. We'll need this for DATABASE_URL.
  • Quicknode account with Hypercore gRPC endpoint. We'll need this for GRPC_ENDPOINT and AUTH_TOKEN.

Getting Started​

1. Clone and install​

git clone https://github.com/quiknode-labs/qn-guide-examples.git

cd qn-guide-examples/sample-dapps/hyperliquid-trading-dashboard

npm install

2. Start PostgreSQL​

If you are using a hosted PostgreSQL instance, skip this step.

npm run db:up

3. Configure environment​

export DATABASE_URL="postgresql://postgres:postgres@localhost:5432/hypercore"
export GRPC_ENDPOINT="your-endpoint.hype-mainnet.quiknode.pro:10000"
export AUTH_TOKEN="your_quicknode_token"

Note: Just paste these with values in two terminal windows. You'll need one window for the Next.js app and another for the database worker.

4. Initialize database​

npm run db:push

5. Start the worker​

npm run worker

This starts the worker process that:

  • Connects to Quicknode HyperCore gRPC
  • Streams live trading events
  • Stores raw trades and aggregated data in PostgreSQL
  • Tracks whale activity and liquidations

You should see:

Ping ok: { count: 1 }
Ingester running
WHALE_MIN_USD: 50000

6. Start the dashboard​

npm run dev

Open http://localhost:3000

Database​

PostgreSQL with Prisma ORM. Two tables:

  • TradeEvent - Individual whale trades and liquidations
  • TradeAggMinute - Per-minute aggregations for trending

Common commands:​

npm run db:up       # Start PostgreSQL container
npm run db:push     # Apply schema
npm run db:studio   # Open Prisma Studio

API Endpoints​


  • GET /api/whales?coin=BTC&windowMin=15&thresholdUsd=50000 - Whale trades
  • GET /api/liquidations?windowMin=15 - Liquidations
  • GET /api/trending?windowMin=15 - Trending coins
  • GET /api/sparklines?windowMin=15&coins=BTC,ETH,SOL - Volume sparklines
  • GET /api/health - Health check

Preview

Preview

Learn More​


Contributions & Feedback
We'd love to hear your feedback and welcome any contributions to this sample app!
To report issues or share feedback, open a GitHub issue in the qn-guide-examples repository.
To contribute, follow these steps:
  1. Fork the repository
  2. Create a feature branch:
    git checkout -b feature/amazing-feature
  3. Commit your changes:
    git commit -m "Add amazing feature"
  4. Push your branch:
    git push origin feature/amazing-feature
  5. Open a Pull Request.
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