M3

Spec sheet

Purpose

M3 is a Prometheus-compatible metrics engine for scaling Prometheus-based monitoring and centralized metrics storage.Read 11 Oct 2026 · m3db.io

Deployment

M3 can be installed with binaries or Docker, and its documentation includes cluster deployment with Kubernetes.Read 11 Oct 2026 · m3db.io

Integrations

The documentation describes integrations with Prometheus, Graphite, Grafana, and InfluxDB.Read 11 Oct 2026 · m3db.io

Support

The project links to a community Slack and GitHub repository.Read 11 Oct 2026 · m3db.io

Compression

The home page reports an optimized compression algorithm with an 11X compression ratio.Read 11 Oct 2026 · m3db.io

Ingestion formats

M3 supports Prometheus, StatsD, and Carbon ingestion formats.Read 11 Oct 2026 · m3db.io

Limitations

M3DB is not intended as a general-purpose time-series database; large-scale backfilling is not currently possible and stored values are optimized for float64.Read 11 Oct 2026 · m3db.io

Open source

M3 is open-sourced under the Apache 2 license, and contributions are welcomed.Read 11 Oct 2026 · m3db.io

Origin

M3 began as an open-source metrics platform developed by Uber’s Observability team in 2014.Read 11 Oct 2026 · m3db.io

Query compatibility

M3 advertises 100% PromQL compatibility and supports Graphite query languages.Read 11 Oct 2026 · m3db.io

Reliability

The home page describes three data replicas with quorum writes and reads for consistency.Read 11 Oct 2026 · m3db.io

Scale

The home page says M3 has been used to store tens of billions of active metric time series.Read 11 Oct 2026 · m3db.io

Storage

M3DB is a distributed time-series database for storing real-time metrics at long retention.Read 11 Oct 2026 · m3db.io

Plans and prices

Every M3 plan and price →

Where Specifiction places it

• Metrics Monitoring Tools#20 of 377.7
• Time-Series Databases#22 of 367.7