Building a data pipeline for real‑time dashboards

Real‑time dashboards are only as good as the pipeline behind them. If your data is stale, your insights are worthless. Here's how we build pipelines that handle thousands of concurrent users with sub‑second latency.

Ingestion: choose the right protocol

For high‑volume data, we recommend streaming ingestion via WebSockets or Kafka. Batch processing can work for reporting, but for dashboards that users expect to refresh instantly, streaming is essential. We support both and let you decide based on your use case.

Processing: decouple and scale

We use a microservices architecture where each stage (ingest, transform, aggregate, serve) can scale independently. This means when one client has a spike, it doesn't affect others.

Storage: time‑series databases

For metrics and event data, time‑series databases like ClickHouse or TimescaleDB give you 10‑100x faster queries than traditional SQL. We also offer caching layers (Redis) for frequently accessed aggregations.

Delivery: API‑first

All our dashboards are powered by a REST API that returns exactly the data needed for the visualisation. This keeps the frontend light and ensures you can reuse the data elsewhere.

Ready to build your own pipeline? We've packaged all this into our white‑label analytics suite. Contact us to see it in action.