Grafana vs Kibana
Compare flexible multi-source dashboards with Elasticsearch-focused analytics and exploration.
Observability
Grafana
Grafana is a visualization platform used to build dashboards across many data sources, including Prometheus, Loki, Elasticsearch, and SQL databases. It is widely used for metrics and observability dashboards.
Observability
Kibana
Kibana is the visualization and exploration interface for Elasticsearch. It is commonly used for searching, analyzing, and visualizing logs and indexed data in the Elastic stack.
Key Differences
Grafana is a general-purpose dashboarding tool across many data sources, while Kibana is tightly aligned with Elasticsearch data.
Grafana is commonly used for metrics-first monitoring, while Kibana is commonly used for deep search and analysis of indexed logs and documents.
Kibana is strongest inside the Elastic stack, while Grafana is stronger in mixed-source observability environments.
Grafana emphasizes dashboard flexibility and time-series visualization, while Kibana emphasizes search, filtering, and log exploration.
Grafana often appears in Prometheus and Loki setups, while Kibana often appears in Elasticsearch logging pipelines.
Grafana is broader across observability stacks, while Kibana is deeper within Elastic-centered workflows.
When to Use
When to use Grafana
Use Grafana when you want dashboards across multiple observability backends and strong time-series visualization for metrics and related telemetry.
When to use Kibana
Use Kibana when your logs and searchable data are centered in Elasticsearch and you need deep filtering, search, and analysis.
Tradeoffs
Grafana is more flexible across tools, but not as specialized for Elastic-native search workflows.
Kibana is powerful for Elasticsearch data, but much less general-purpose outside the Elastic ecosystem.
Grafana is often the better dashboard layer across mixed stacks, while Kibana is often the better analysis layer within Elastic stacks.
Common Mistakes
Expecting Kibana to act like a general dashboard platform across many unrelated data sources.
Choosing Grafana when deep Elasticsearch-centric search and document analysis is the real need.
Assuming both tools solve the same observability use cases equally well.
Interview Tip
A clean short answer is: Grafana is broader for dashboards across data sources, while Kibana is deeper for Elasticsearch-based search and log analysis.