Creating Enterprise Dashboards: Grafana vs. Kibana
By: Deepak Kumar
Tags: Grafana, Dashboard, Monitoring Dashboard, Application Monitoring, Kibana

IT firms today are becoming more and more reliable using the huge volume of data that is produced by the application services that they use. To understand and organize the structural needs for these applications, observability is being looked like the future of the IT industry. Benefits of which include faster debugging, in-depth root cause analysis, improved environment awareness, thus performance becomes more efficient.

Dashboards are what acts as an interface for most of the observability tools that we use today, which in real time presents the analyzed data in the form of visualizations required for monitoring these application services. We will discuss two such open-source visualization tools.

Grafana and Kibana are two widely popular data visualization tools, we will compare these tools primarily in terms of their data visualization abilities for each to create enterprise ready dashboards. We will also investigate some important factors which make these tools different from each other such as Integration of data sources, Role based access, Querying.

Sample grafana dashboard

Sample kibana dashboard

Data visualization abilities: Grafana is a lightweight standalone tool is primarily used for visualizing timeseries metric data. Visualizations created by grafana are called ‘panels’. These panels are very insightful as they are enriched with small details which gives a lot of flexibility to the end user to control how the data is being presented. This makes grafana dashboards very attractive and user friendly. Grafana’s UI is designed primarily for analyzing timeseries data and not for exploring the raw data, which makes the tool a little complex for new users. Data visualization capabilities for grafana are limited and does not include advanced features like machine learning, APM etc. Grafana community also comes with a dashboard library where you can share and search through thousands of existing dashboards according to individual needs.

Kibana on the other hand is an advanced tool which provides much more than data visualization capabilities. Being an integrated part of the ELK(elasticsearch, logstash, kibana) stack and its full-text search capabilities, it is primarily used for log monitoring. Visualizations created with Kibana are very standard in nature and do not provide the flexibility that Grafana offers. TSVB (timeseries data visualizer) provides some flexibility to control the data presentation but still lacks in the details in comparison to Grafana. Unlike Grafana, kibana offers features like anomaly detection, APM which can furthur enhance its data visualization abilities.

Integration of data sources: Grafana is a cross platform tool. It officially provides integration with 16 different data sources like AWS cloudwatch, elasticsearch, graphite, influxDB, prometheus etc. Apart from this, grafana allows to add a wide variety of data sources to be added through their data source plugin feature.

Kibana, being a native of ELK stack supports only elasticsearch as the data source, which makes the setup very simple. Being the only data source, elasticsearch has a very well-developed integration with kibana, thus providing excellent functionalities and features with great performance.

Role based access UI in grafana

API key UI in grafana

Role based access: Grafana comes with built in user control and authentication mechanism which allows you to restrict and control dashboard access. Different organizational roles can also be defined with grafana tool with different access controls, which makes grafana suitable for working on dashboards as an organization. Grafana also allows us to use ‘API keys’ based on different roles which can be used to access the dashboard data from third-party services, thus it is easy to provide read-only access to these external services.

Kibana does not support any such role-based access for users, all dashboards are by default accessible to the public. To achieve access control and authentication capabilities, the most common way is to use X-Pack the elastic commercial feature.

Grafana query UI for InfluxDB data source

Kibana query DSL example

Querying: Grafana provides a query editor to explore the data from its various data sources. Different data sources come with their own query language. Grafana also provides a dedicated UI to manipulate queries instead of writing them for some data sources like influxDB etc.

Kibana comes with much more powerful querying abilities for the dedicated elasticsearch data store. Searching through logs with full-text search is one of kibana’s strengths. It used query DSL (domain specific language) based on json to define queries. DSL is simple, but a little different for first time users.

In conclusion, both Grafana and Kibana are greate data visualization tools. Choosing a suitable one depends on the user requirements. Grafana has an edge over Kibana for time series metric data, and Kibana is well suited for log monitoring.