# Unimeter

> Open source usage metering engine. Record events, aggregate in real time, query billing totals in milliseconds.

Unimeter is an alternative to Lago, Amberflo, and similar usage-based billing platforms. It is a single compiled binary with zero runtime dependencies, built for high throughput (500K+ events/sec) and sub-millisecond query latency. Events go in, usage totals come out.

## Docs

- [What is Unimeter](https://unimeter.io/what-is-unimeter/): Overview and use cases
- [Quickstart](https://unimeter.io/quickstart/): Run Unimeter and record your first event
- [Events and metrics](https://unimeter.io/concepts/events-and-metrics/): Core data model
- [Metric types](https://unimeter.io/concepts/metric-types/): COUNT, SUM, MAX, LATEST, COUNT_UNIQUE
- [Filters and dimensions](https://unimeter.io/concepts/filters/): Slice usage by tags
- [Alerts](https://unimeter.io/concepts/alerts/): Threshold-based notifications
- [Go SDK](https://unimeter.io/sdk/go/): Full Go client reference
- [Python SDK](https://unimeter.io/sdk/python/): Full Python async client reference
- [Stripe integration](https://unimeter.io/guides/stripe/): Connect Unimeter to Stripe billing
- [Running a cluster](https://unimeter.io/operations/cluster/): Multi-node deployment
- [Observability](https://unimeter.io/operations/observability/): Prometheus metrics and Grafana
- [Architecture](https://unimeter.io/operations/architecture/): How it stays fast

## SDKs

- Go: `go get github.com/unimeter/go-unimeter@latest`
- Python: `pip install unimeter-python` (Python 3.11+, asyncio)

## Full docs for LLMs

For the complete documentation in a single file optimized for LLM context, see [llms-full.txt](https://unimeter.io/llms-full.txt).