Prometheus vs InfluxDB: Which Metrics Database?
Prometheus is a pull-based monitoring system built around metrics and alerting; InfluxDB is a general-purpose time-series database for metrics and events.
Prometheus scrapes targets on a pull model, stores dimensional metrics, and pairs with Alertmanager and PromQL for monitoring-first workflows. InfluxDB accepts pushed writes, supports higher-cardinality event data, and offers Flux/InfluxQL plus longer-term storage options. Prometheus wins for Kubernetes-native monitoring and alerting; InfluxDB wins for event-style time-series, IoT, and flexible retention.
| Prometheus | InfluxDB | |
|---|---|---|
| Model | Pull (scrape) | Push (write) |
| Query | PromQL | Flux / InfluxQL |
| Focus | Monitoring + alerting | General time-series |
| Cardinality | Moderate | Higher tolerance |
| Best for | K8s metrics, alerts | IoT, events, retention |
Use case and model
Prometheus suits cloud-native monitoring where targets expose metrics for scraping and alerting matters most. InfluxDB suits ingesting pushed metrics and events from devices or apps, with flexible downsampling and retention policies for long histories.
Ops and CI fit
Prometheus is simple to run for short-term metrics but needs Thanos or Cortex for long retention; InfluxDB handles retention natively. Both are exercised in CI against ephemeral instances, where faster runners speed integration and query tests.
The verdict
Want Kubernetes-native monitoring with first-class alerting: Prometheus. Want a flexible time-series store for events, IoT, and built-in retention: InfluxDB. Pick by whether monitoring/alerting or general time-series storage dominates.