Traditional dashboards refresh hourly. For service degradation detection, trading, or fraud — batch is too slow. Real-time requires rethinking the entire pipeline.
Receives pre-aggregated data, pushes to clients.| ClickHouse | Pure OLAP | <1s | Growing |
| TimescaleDB | Mixed, PG | 2-5s | PostgreSQL |
| Druid | High concurrency | <1s | Complex ops |
| InfluxDB | Metrics | 1-3s | Monitoring |
Dashboard speed is data architecture not frontend. Pre-aggregate, purpose-built DB, WebSocket. Get layers right and sub-second is straightforward.
Building real-time analytics dashboards with sub-second latency requires four architectural layers: event streaming ingestion (Kafka for 100K+ events/sec or Redis Streams for simpler needs), time-series database storage (which outperforms SQL 10-100x for analytics queries), pre-aggregation at ingestion time for instant queries, and WebSocket delivery which is 10x faster than polling while using 90% less bandwidth.
Key Takeaways
- Event streaming decouples producers from consumers
- Time-series DBs outperform SQL 10-100x for analytics
- Pre-aggregation at ingestion = sub-second queries
- WebSocket: 10x faster than polling, 90% less bandwidth
- Data architecture > frontend framework for speed
Frequently Asked Questions
Key Terms
- Event Streaming
- Events published to durable log consumed by multiple subscribers.
- Time-Series DB
- Optimized for timestamped data with compression and aggregation.
- Pre-Aggregation
- Computing summaries at ingestion not query time.
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Walk Us Through Your DataSummary
Real-time dashboards need event streaming ingestion, time-series storage, pre-aggregation, and WebSocket delivery.