Time-series & event data

What changes when time is the dominant dimension?

Handle append-heavy metrics and events using time partitioning, retention, compression, downsampling, and streaming logs.

Systems compared

• TimescaleDB
• InfluxDB
• Prometheus
• Kafka

Open the engine

1. Time partitioning
2. Retention and downsampling
3. Compression
4. Event-time semantics
5. Logs and consumer offsets

Reconstruction lab

Design an observability pipeline and choose where metrics, logs, and durable events should live.