Real-time analytics is seductive. But real-time comes with real costs—in complexity, money, and engineering time.
The Latency Spectrum
Batch - Data is processed in scheduled chunks (daily, hourly).
Micro-batch - Frequent small batches (every few minutes).
Near real-time - Sub-minute latency.
Real-time streaming - Milliseconds to seconds.
When Real-Time Matters
Fraud Detection - Credit card decisions need to happen now.
Operational Monitoring - Knowing your servers are down 15 minutes later is too late.
User-Facing Recommendations - Near real-time updates improve engagement.
When You Probably Don't Need Real-Time
Executive Dashboards - Daily or hourly refresh is usually fine.
Marketing Analytics - Campaign metrics don't change actions minute by minute.
Historical Reporting - Batch was built for this.
The Hidden Costs of Real-Time
Complexity, 24/7 infrastructure costs, data quality challenges, and ordering/consistency issues.
The Pragmatic Middle Ground
Micro-batch (every 5 minutes) often provides the best balance—simpler than true streaming while still "fast enough."