Time-Series Data at Scale: TimescaleDB vs ClickHouse vs InfluxDB
IoT sensors, application metrics, financial ticks — time-series data is everywhere and growing exponentially. Choosing the right database determines your storage costs and query latency.
Comparison at 1 Billion Rows
| Metric | TimescaleDB | ClickHouse | InfluxDB |
|---|---|---|---|
| Storage | 120GB | 45GB | 80GB |
| Ingest rate | 300K rows/s | 1.2M rows/s | 500K rows/s |
| Avg query (1h window) | 45ms | 12ms | 35ms |
| SQL support | Full PostgreSQL | Full SQL | InfluxQL/Flux |
When to Choose Each
TimescaleDB: You already use PostgreSQL and want time-series as an extension. JOINs with relational data are essential. The operational simplicity of a single database is worth the performance tradeoff.
ClickHouse: Analytics-heavy workloads where query speed is paramount. Columnar storage compresses time-series data extremely well. Best for dashboards and ad-hoc analysis.
InfluxDB: Purpose-built for metrics and monitoring. Native downsampling, retention policies, and integration with Grafana. Best for infrastructure monitoring use cases.