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From role-database
Guides selection, operations, and best practices for 14 time-series databases like InfluxDB, Prometheus, TimescaleDB for metrics, IoT, financial, observability storage design.
How this skill is triggered — by the user, by Claude, or both
Slash command
/role-database:time-series-databasesThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
You are a time-series database specialist informed by the Software Engineer by RN competency matrix.
You are a time-series database specialist informed by the Software Engineer by RN competency matrix.
Use when building time-series storage for metrics pipelines, IoT sensor data, financial tick data, observability backends, or any workload where time is the primary dimension.
| Database | Best For | Ingestion | Managed |
|---|---|---|---|
| InfluxDB 3.0 | General-purpose TSDB, Parquet storage | 1M+ pts/s | InfluxDB Cloud |
| Prometheus | Metrics scraping, Kubernetes, alerting | 10M+ (scrape) | Grafana Cloud, AWS AMP |
| TimescaleDB | SQL time-series on PostgreSQL | 1M+ pts/s | Timescale Cloud |
| QuestDB | High-ingestion SQL, ASOF joins | 1.4M+ pts/s | QuestDB Cloud |
| VictoriaMetrics | Prometheus replacement, lower cost | 10M+ pts/s | VictoriaMetrics Cloud |
| TDengine | IoT super-table model, streaming | 10M+ pts/s | TDengine Cloud |
| KDB+ | Financial tick data, q language | 100M+ pts/s | KX Cloud |
| Timestream | Serverless AWS TSDB | 1M+ pts/s | AWS Managed |
Load the relevant reference file when you need implementation details:
npx claudepluginhub rnavarych/alpha-engineer --plugin role-databaseGuides IoT time-series data management: selects databases like InfluxDB/TimescaleDB/Prometheus, designs tag/field schemas, implements downsampling/retention/compression, compares processing modes, and optimizes Grafana dashboards.
Provides operational guidance for 12 columnar and wide-column databases including Cassandra, ScyllaDB, ClickHouse for configuring, tuning, and high-write analytics workloads.
Designs append-heavy tables for metrics, events, and logs with time-based partitioning, retention policies, and efficient aggregation using PostgreSQL.