Time Series Database Example in SQL

A proposed architecture for customer-facing API observability treats request logs as wide events in ClickHouse or Tinybird rather than as traditional time-series labels, enabling per-tenant, per-route latency and error dashboards while keeping unbounded identifiers such as user_id out of hot aggregations. Raw events are retained for 14 days for drill-down, ordered by tenant, path, and timestamp, while materialized one-minute rollups using aggregate states retain 90 days and support fast tenant-filtered chart queries, late-event corrections based on event time, and p95 latency calculations. The design targets 5,000 events per second, 50,000 tenants, bounded route cardinality, sub-100-millisecond tile queries, and data visibility within five seconds, with batch or Kafka ingestion recommended to avoid merge backlogs. Tinybird is presented as a managed way to expose the ClickHouse rollups as token-scoped HTTP endpoints, while Prometheus and similar series-oriented databases remain suitable for bounded infrastructure metrics such as host scrapes but risk series explosion when high-cardinality user identifiers are modeled as labels.

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