Comparing Grafana and Kibana/Timelion for Time‑Series Data Visualization

Grafana has quickly become a de‑facto DevOps tool for real‑time monitoring of time‑series metrics, supporting multiple back‑ends such as InfluxDB, Graphite, Elasticsearch and many plugin‑based sources.

Kibana, the front‑end of the Elastic Stack, complements Beats, Logstash and Elasticsearch, and since version 5.x includes Timelion for interactive time‑series charts.

The article demonstrates a performance‑analysis dashboard that uses both Grafana and Kibana to present different data views.

Timelion Overview

Timelion, pronounced “Timeline”, is bundled with Kibana 5+ and defines charts via a custom query language. A simple example uses the expression .es(*) to show the total document count over time in Elasticsearch.

Each Timelion expression starts with a data‑source function followed by a chain of functions; over 20 functions are available, grouped into data source, data manipulation, and visual styling.

Data source – default Elasticsearch, with optional APIs like World Bank or Quandl.

Data manipulation – e.g., .es(*).movingaverage(12) adds a moving average.

Visual styling – e.g.,

.es(index=ash*).lines(1,fill=1).title('RunningQueries').legend(none).label(false)

.

Timelion’s query box offers autocomplete and online help, though the expression editor can become cramped for complex visualizations.

Grafana Overview

Grafana is an open‑source, feature‑rich dashboard and graph editor praised for its simplicity, modern UI, and extensive plugin ecosystem.

Most configuration is performed through a comprehensive graphical editor, but advanced queries can be entered manually to access Elasticsearch, InfluxDB, Graphite, etc.

Grafana’s alerting engine allows attaching rules to panels, storing them separately for evaluation.

Presentation Differences

Grafana’s graph editor provides a clear UI with many formatting options, including automatic unit scaling (Byte → MB → GB) and support for negative values, which Timelion lacks.

Grafana can render metric values directly in the legend, a feature Timelion does not provide.

Interaction Differences

Both tools support time‑range selection by dragging, but Kibana offers richer interaction, such as instant text search and drill‑down by clicking data points.

Timelion can inherit Kibana dashboard filters via the kibana='true' parameter in the .es() function, e.g.,

.es(index=dms_*,metric='avg:obips1-Current_Disk_Usage',fit='nearest',kibana='true')

.

Grafana allows global variables for dashboard‑wide filtering, though this requires custom setup.

Conclusion

Grafana excels in flexible graph editing, unit handling, and alerting, making it ideal for pure time‑series dashboards, while Kibana (with Timelion) offers powerful multidimensional exploration and seamless integration with the Elastic Stack. The author recommends using both together to leverage their complementary strengths.