Open-Source Observability · grafana

mimir

Grafana Mimir is an open-source, horizontally scalable long-term storage system for Prometheus metrics. It handles massive metric volumes (up to 1 billion active time series), supports multi-tenancy, and integrates with standard object storage (S3, GCS, Azure).

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Source: GitHub — github.com/grafana/mimir

5.2k

GitHub stars

797

Forks

Primary language

AGPL-3.0

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	grafana/mimir
Owner	grafana
Primary language	Go
License	AGPL-3.0 — OSI-approved
Stars	5.2k
Forks	797
Open issues	785
Latest release	mimir-3.1.2 (2026-06-24)
Last updated	2026-07-08
Source	https://github.com/grafana/mimir

What mimir is

Written in Go, Mimir provides a distributed time-series database backend for Prometheus with horizontal scaling, replication for high availability, multi-tenant query isolation, and object-store persistence. It supports Prometheus remote-write protocol and OTLP ingestion, with query parallelization for high-cardinality workloads.

Quickstart

Get the mimir source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/grafana/mimir.git2cd mimir3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Multi-team metric aggregation at scale

Share a single Mimir cluster across teams or business units with isolated data, fair capacity allocation, and tenant-level quality-of-service controls.

Long-term metric retention without on-prem storage

Offload Prometheus data to cost-effective object storage (S3, GCS, Azure) for years-long retention while maintaining query performance via distributed query execution.

High-availability metrics infrastructure

Deploy across multiple machines with automatic replication and zero-downtime upgrades, eliminating single points of failure for metric ingestion and alerting.

Implementation considerations

Object storage (S3, GCS, Azure, Swift) must be configured upfront; choose provider based on latency, cost, and existing cloud footprint.
Plan for distributed deployment with service discovery, load balancing, and orchestration (typically Kubernetes); monolithic mode suitable only for evaluation.
Configure multi-tenancy tenant IDs, rate limits, and cardinality controls early to prevent one tenant from impacting others.
Establish retention policies and compaction windows before production; object storage costs scale with data volume and query complexity.
Test migration path from Prometheus/Thanos/Cortex using provided documentation to validate schema compatibility and query behavior.

When to avoid it — and what to weigh

Strict proprietary-only software requirements — Mimir is AGPL-3.0 licensed. Commercial use requires careful license compliance review or a commercial agreement with Grafana Labs; cannot be simply embedded in closed-source products without disclosure.
Single-binary simplicity is mandatory — While monolithic mode exists, production deployments typically require distributed architecture, orchestration (Kubernetes), and operational expertise. Not a drop-in replacement for single Prometheus.
Low operational overhead and minimal documentation tolerance — Requires understanding of time-series architecture, object storage configuration, and horizontal scaling patterns. Setup and tuning demand deeper expertise than basic Prometheus.
Already heavily invested in non-Prometheus metrics backends — Mimir is optimized for Prometheus data model and ingestion protocol. Retrofitting from InfluxDB, Graphite, or other time-series systems may require significant rework.

License & commercial use

Licensed under AGPL-3.0-only. This is a copyleft open-source license requiring that any software linking to or distributing Mimir must also be open-sourced under AGPL-3.0 or compatible terms. Grafana Labs may offer commercial licensing alternatives for proprietary use.

AGPL-3.0 is a strong copyleft license. Commercial use in proprietary software is not permitted under the open-source license alone. Organizations using Mimir as a service (SaaS) or modifying it internally face disclosure obligations. Requires explicit commercial license negotiation with Grafana Labs or legal review before deployment in closed-source products.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Needs review
Deployment complexity	High
DEV.co fit	Good
Assessment confidence	High

Security considerations

Multi-tenant isolation enforced via tenant ID headers; ensure API gateway authenticates and validates tenant ID claims. Object storage access credentials should use IAM roles or secrets management, not embedded keys. Network policies should restrict intra-cluster communication. No security audit report or disclosure policy provided in data; review Grafana's security advisories separately. AGPL-3.0 source availability aids code review but does not imply security certification.

Alternatives to consider

Thanos

Apache-2.0 licensed, adds long-term storage layer to Prometheus with S3 backend, but Grafana Mimir offers integrated multi-tenancy, native query federation, and operational simplification as a unified replacement.

Cortex

Apache-2.0 licensed predecessor to Mimir with similar architecture; Mimir is the maintained forward path, offering improved query performance and simplified deployment.

VictoriaMetrics

Single-vendor proprietary option with Apache-2.0 open-core licensing; offers similar horizontal scaling and long-term storage but requires commercial license for certain features and lacks AGPL copyleft obligations.

Software development agency

Build on mimir with DEV.co software developers

Our engineers can help assess AGPL-3.0 compliance, design distributed deployments, and validate multi-tenancy configurations for your observability stack. Contact us for a technical review.

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mimir FAQ

Can we use Mimir if we only need local object storage or NFS?

Mimir supports S3-compatible object storage APIs. Local MinIO instances or NFS-backed S3 proxies can be used for development/testing, but cloud-native object storage (S3, GCS, Azure) is recommended for production durability and cost efficiency.

What is the difference between Mimir and Cortex?

Cortex is the predecessor; Mimir is Grafana's maintained successor with improved query performance, better operational defaults, simplified configuration, and is the recommended choice for new deployments.

Do we need to modify our Prometheus configuration to use Mimir?

No major changes required. Add remote_write stanza pointing to Mimir ingester URL and include tenant ID header; existing scrape configs remain unchanged. See migration guides for Prometheus-to-Mimir setup.

Is Mimir suitable for small teams with limited operational capacity?

Monolithic mode simplifies single-node deployment, but production use requires distributed systems expertise. Small teams may prefer managed solutions or SaaS offerings; Grafana Cloud Metrics provides hosted Mimir.

Work with a software development agency

DEV.co helps companies turn open-source tools like mimir into production software. Our software development services cover the full lifecycle — architecture, web development, integration, and maintenance — delivered by software developers and web developers who ship. Engage our software development agency to implement or customize it for your open-source observability stack.

Evaluating Grafana Mimir for your metrics infrastructure?

Our engineers can help assess AGPL-3.0 compliance, design distributed deployments, and validate multi-tenancy configurations for your observability stack. Contact us for a technical review.

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