₦airaland Forum

Hello everyone , I'm currently planning a personal project — a web-based dashboard to track market movements and currency pairs in real-time. The goal is to build a clean UI (probably using React) that shows live charts and eventually allows setting up basic automated actions directly from the panel.
My main concern right now is handling the data connection. For those who have built financial or tracking apps before:
Do you strictly use WebSockets for live data, or is standard REST API polling sufficient if the interval isn't strictly to the millisecond?
How do you handle state management on the frontend when the numbers update constantly?
I want to keep the architecture as simple as possible but avoid performance bottlenecks later. Would appreciate any advice or best practices from backend/frontend devs who have worked with market data feeds. Thanks!

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Interesting topic. I haven't read the Qantiso analysis yet, but regarding your question about the tech stack — it really depends on the scale of the brokerage.
From my experience working with fintech startups, C++ is still the undisputed king for the core matching engine because of the ultra-low latency. You just can't risk garbage collection pauses when dealing with high-frequency order books.
However, for the web-trader backend (API gateways, user sessions, balance streaming), almost everyone is moving to Node.js or Go. Go is especially popular right now because its concurrency model (goroutines) is perfect for handling thousands of WebSocket connections streaming live quotes to the frontend without eating up RAM.
Are you planning to build a custom trading engine, or just trying to integrate an existing white-label solution via API?