influxdb

InfluxDB time-series database for metrics and IoT. Use for time-series data.

7 stars

byG1Joshi

View on GitHub Installation ↓

Best use case

influxdb is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

InfluxDB time-series database for metrics and IoT. Use for time-series data.

Teams using influxdb should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/influxdb/SKILL.md --create-dirs "https://raw.githubusercontent.com/G1Joshi/Agent-Skills/main/skills/databases/influxdb/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/influxdb/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How influxdb Compares

Feature / Agent	influxdb	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

InfluxDB time-series database for metrics and IoT. Use for time-series data.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# InfluxDB

InfluxDB is a purpos-built time series database. Version 3.0 (IOx) is a complete rewrite in Rust, using Parquet/Arrow for massive performance gains.

## When to Use

- **IoT Metrics**: Sensor data from millions of devices.
- **DevOps Monitoring**: CPU, RAM, Disk usage over time.
- **Financial Ticks**: High frequency trading data.

## Quick Start (InfluxQL / SQL)

InfluxDB 3.0 supports SQL!

```sql
SELECT room, MEAN(temp)
FROM sensors
WHERE time > now() - 1h
GROUP BY room
```

## Core Concepts

### Push vs Pull

InfluxDB is "Push" based (Telegraf agents push data to it). Prometheus is "Pull" based.

### High Cardinality (v3)

The old InfluxDB struggled if you had too many "Tags" (Cardinality). The new IOx engine (Parquet-based) handles unlimited cardinality.

### Downsampling

Automatically aggregating high-resolution data (1s) into lower resolution (1m, 1h) to save space.

## Best Practices (2025)

**Do**:

- **Use SQL**: InfluxDB 3.0 prioritizes SQL (FlightSQL) over the old Flux language.
- **Use Parquet**: Understand that data is stored in Parquet (Object Storage friendly).
- **Tag wisely**: Even though v3 handles cardinality, proper schema design (Measurement vs Tag vs Field) still matters for query speed.

**Don't**:

- **Don't use Flux for new projects**: It is being deprecated in favor of SQL and Python.

## References

- [InfluxDB Documentation](https://docs.influxdata.com/)