When our clients asked for real-time dashboards to visualize their market data, we knew performance would be the defining challenge. Displaying thousands of data points with live updates, while keeping the UI responsive, required careful architectural decisions from the start.
We chose Next.js for its hybrid rendering capabilities. Static elements like navigation, filters, and layout are server-rendered for instant page loads. Dynamic data sections use client-side rendering with streaming, so users see the dashboard shell immediately while data populates progressively.
On the backend, PostgreSQL handles our structured data with carefully designed materialized views. Instead of running expensive aggregation queries on every dashboard load, we pre-compute common views (daily averages, weekly trends, category rollups) and refresh them on a schedule. This reduced our p95 query time from 2.3 seconds to under 50 milliseconds.
For real-time updates, we implemented a WebSocket layer that pushes incremental data changes to connected clients. Rather than polling the entire dataset, the frontend receives only the deltas, small JSON patches describing what changed. This keeps bandwidth usage minimal even with hundreds of simultaneous users.
Chart rendering was another performance bottleneck. Rendering 10,000+ data points with a typical charting library would freeze the browser. We implemented data decimation, intelligently reducing the number of rendered points based on the current zoom level, and used canvas-based rendering instead of SVG for datasets above a threshold.
The result is a dashboard that loads in under 1 second, handles live updates without flicker, and remains smooth even on mobile devices. Our clients can monitor competitor pricing, track sentiment shifts, and spot emerging trends, all in real time.
