Prometheus vs Grafana (July 2026): Side-by-Side Comparison
TL;DR: This is not a versus. Prometheus is a metrics database that collects, stores, and alerts; Grafana is the visualization layer on top. The real questions are how to run them together and when to pay for managed versions.
Spec comparison
| Spec | Prometheus | Grafana |
|---|---|---|
| Category | Metrics database + alerting (TSDB) | Visualization + dashboards |
| License | Apache 2.0 | AGPLv3 (OSS) + commercial |
| Data collection | Pull-based scraping of /metrics endpoints | None, queries external data sources |
| Storage | Local TSDB + remote-write (Thanos, Mimir) | Stateless, stores dashboards, not metrics |
| Query language | PromQL (defines the standard) | PromQL, LogQL, TraceQL, SQL, per data source |
| Alerting | Recording/alert rules + Alertmanager | Grafana Alerting (unified, multi-source) |
| Data sources | Is one (exposes an HTTP query API) | 150+ (Prometheus, Loki, Tempo, CloudWatch, SQL…) |
| Managed options | Amazon Managed Prometheus, Grafana Cloud (Mimir) | Grafana Cloud, Amazon Managed Grafana |
| CNCF status | Graduated (second project after Kubernetes) | Not CNCF (Grafana Labs) |
| Best for | Collecting and storing infrastructure metrics | Visualizing metrics, logs, and traces from anywhere |
Feature matrix
| Capability | Prometheus | Grafana |
|---|---|---|
| Stores time-series metrics | ✓ | ✗ |
| Scrapes exporters / instrumented apps | ✓ | ✗ |
| Rich dashboards & visualization | ~ | ✓ |
| Alert rule evaluation | ✓ | ✓ |
| Query multiple data sources at once | ✗ | ✓ |
| Logs and traces support | ✗ | ✓ |
| Long-term / horizontally scaled storage | ~ | ✗ |
| Built-in auth, SSO, and RBAC | ✗ | ✓ |
| PromQL support | ✓ | ✓ |
| Works without the other | ✓ | ✓ |
What Prometheus actually does
Prometheus is a pull-based time-series database. It scrapes /metrics endpoints exposed by your applications and by exporters (node_exporter for hosts, kube-state-metrics for Kubernetes, cAdvisor for containers), stores the samples in its local TSDB, and continuously evaluates recording and alerting rules written in PromQL. When a rule fires, Alertmanager handles deduplication, grouping, routing, and silencing. Its one deliberate weakness is durability at scale: local storage is single-node, so long retention and high availability come from remote-write targets like Thanos, Cortex, or Grafana Mimir. Its other weakness is presentation: the built-in expression browser is a debugging tool, not a dashboard. That is the gap Grafana fills.
What Grafana actually does
Grafana is a visualization and analytics front-end that owns none of your telemetry. It connects to 150+ data sources (Prometheus first among them, but also Loki for logs, Tempo for traces, CloudWatch, Elasticsearch, and SQL databases) and renders them into dashboards with variables, annotations, and unified alerting. Because it is stateless with respect to metrics, Grafana scales by adding data sources, not storage. Grafana Labs has also built out the storage side of the ecosystem (Mimir for metrics, Loki for logs, Tempo for traces), which is why "Grafana" increasingly refers to a full stack rather than just the dashboard tool. If you are evaluating that full stack against alternatives, see our Grafana alternatives breakdown.
The standard combination
The dominant open-source monitoring stack in 2026 is still Prometheus + Grafana: Prometheus (or a Prometheus-compatible backend) scrapes and stores, Grafana queries and displays. On Kubernetes, the kube-prometheus-stack Helm chart installs both plus Alertmanager and a set of curated dashboards in one release. Teams that outgrow single-node Prometheus typically keep the same PromQL and dashboards and swap the storage layer for Mimir, Thanos, or a managed service: the Grafana layer does not change. The main commercial alternative is an all-in-one SaaS platform; if you are weighing that trade-off, our Datadog alternatives guide covers where the open-source stack wins and loses on cost.
Which should you choose?
- If the question is "which one do I install": install both. They solve different halves of the same problem.
- Need metrics collection and alerting only, no dashboards for a wider team? Prometheus alone is enough to start.
- Already have metrics in CloudWatch, InfluxDB, or SQL and just need dashboards? Grafana alone, no Prometheus required.
- On Kubernetes? Deploy kube-prometheus-stack and get both, wired together, in one Helm release.
- Retention beyond a few weeks or multi-cluster views? Add Mimir or Thanos via remote-write, or use Amazon Managed Prometheus / Grafana Cloud.
- Watch the license if you embed Grafana in a product: OSS Grafana is AGPLv3, which is why some vendors ship forks or pay for commercial licensing.
FAQ
Is Grafana a replacement for Prometheus?
No. Grafana does not collect or store metrics: it visualizes data that lives elsewhere. Prometheus is a time-series database that scrapes and stores metrics and evaluates alert rules. In practice Grafana is the most common front-end for a Prometheus back-end, so the two are complements, not competitors.
Do I need both Prometheus and Grafana?
For most production monitoring stacks, yes. Prometheus alone gives you an expression browser that is fine for debugging but not for team dashboards; Grafana alone has no metrics to show until you connect a data source. The standard open-source stack is Prometheus for collection, storage, and alerting, with Grafana on top for dashboards.
Can Grafana store metrics without Prometheus?
Not by itself. Grafana is stateless with respect to metrics: it only stores dashboards, users, and alert configuration. If you want a Grafana-ecosystem metrics database, Grafana Labs ships Mimir, a horizontally scalable Prometheus-compatible TSDB, which is also what backs metrics in Grafana Cloud.
What are the managed options for Prometheus and Grafana?
For Prometheus-compatible storage: Amazon Managed Service for Prometheus and Grafana Cloud (backed by Mimir) are the two mainstream choices. For Grafana itself: Grafana Cloud and Amazon Managed Grafana. Many teams run a small local Prometheus per cluster and remote-write to a managed backend to avoid operating long-term storage.
Does Grafana Alerting replace Alertmanager?
It can, but many teams keep both. Prometheus Alertmanager is battle-tested for routing, grouping, and silencing alerts defined as Prometheus rules. Grafana Alerting adds a unified UI that can evaluate alerts across multiple data sources (metrics, logs, SQL) and can either manage its own rules or act as a front-end to an existing Alertmanager.
Beyond metrics: watching what AI agents do
Prometheus and Grafana tell you what your infrastructure is doing. They do not tell you what your AI agents are doing to that infrastructure, which agent called which API, with which identity, under which policy, at what cost. That is a different telemetry problem, and it is the one Swfte Nexus solves: it captures every AI-agent action via runtime hooks, enforces policy in-flight, and traces agents, identities, and connections the way Prometheus traces CPU and memory. If your dashboards are green but an agent is quietly burning spend or touching systems it should not, metrics alone will not show it, see LLM observability for how the two layers fit together.