Tool Comparison · 2026 Edition

Kibana vs Grafana: Log Analysis or Multi-Source Dashboards?

Kibana is tightly coupled to Elasticsearch and excels at log analysis. Grafana is data-source-agnostic and excels at metrics dashboards. They are often used together; here's how to think about each.

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TL;DR

Key takeaways

Kibana is the official UI for Elasticsearch — Discover, Lens, Maps, APM UI, Security UI, Observability UI. Tightly tied to the Elastic Stack.
Grafana is a multi-source dashboard tool: Prometheus, Loki, Tempo, InfluxDB, Elasticsearch, MySQL, CloudWatch — 60+ data sources.
Kibana wins for log analysis against Elasticsearch; Grafana wins for metrics against Prometheus.
Many teams use both: Kibana for logs, Grafana for metrics dashboards.

Data source orientation

Kibana only queries Elasticsearch. All its features (Discover, Lens, Maps, APM) assume Elasticsearch indices as the backing store.

Grafana is data-source-agnostic. You can mix Prometheus, Loki, and Elasticsearch panels in a single dashboard.

If your telemetry already lives in Elasticsearch, Kibana is the natural choice. If you have multiple backends, Grafana is more flexible.

Logs, metrics, and traces

Kibana Discover + Lens is the best UX for Elasticsearch log analysis — faster than Grafana's Elasticsearch panel.

Grafana + Loki (log aggregation) + LogQL is Grafana's answer; good, but Elasticsearch + Kibana remains stronger at full-text search.

For metrics on Prometheus, Grafana is more polished than Kibana's Metrics UI.

Both support distributed tracing (Grafana via Tempo; Kibana via Elastic APM / OTel).

Licensing and pricing

Kibana (Elastic License) is free for self-hosted use with basic features; paid tiers unlock security, alerting, SIEM, and ML.

Grafana OSS is Apache 2.0 — fully free. Grafana Enterprise and Grafana Cloud have paid tiers.

At scale, both platforms carry costs: Elastic Cloud / Elastic Stack ops for Kibana; Grafana + Prometheus + Loki + Tempo + ops for Grafana.

Managed alternative

Atatus provides managed log search (with full-text search comparable to Kibana) plus metrics dashboards (comparable to Grafana) in one UI.

You don't operate Elasticsearch clusters or the LGTM stack.

OTel-native and compatible with Prometheus exporters + Filebeat / Fluent Bit input.

Side-by-side comparison

Kibana

Pros

Best Elasticsearch log UX
Discover, Lens, Maps
APM UI, SIEM UI
Full-text search strength

Cons

Elasticsearch only
Elastic License (not pure OSS)
Metrics UX weaker than Grafana

Pricing: Free (basic) / paid tiers

Best for: Teams using Elastic Stack

Grafana

Pros

60+ data sources
Mix sources in one dashboard
Metrics-first UX
Apache 2.0 OSS
Massive community

Cons

Log UX weaker than Kibana
No native data store

Pricing: Free OSS / Grafana Cloud (usage)

Best for: Metrics-first, multi-source teams

Atatus

Pros

Managed logs + metrics + traces
Full-text log search
No cluster to run
Flat per-host pricing

Cons

Fewer data-source adapters than Grafana

Pricing: Flat per-host, all signals included

Best for: Teams tired of running Elastic + LGTM stack

Verdict

Kibana wins for Elasticsearch-centric log analysis; Grafana wins for metrics dashboards against multiple sources. If you're running both an Elastic Stack and a Grafana stack, that's two ops teams' worth of overhead — Atatus consolidates both into one managed platform.