Kamon vs Kibana

Overview

Kibana

Stacks20.6K

Followers16.4K

Votes262

GitHub Stars20.8K

Forks8.5K

Kamon

Stacks7

Followers12

Votes3

Kamon vs Kibana: What are the differences?

Introduction: Kamon and Kibana are both tools used for monitoring and analyzing applications, but they have key differences that set them apart.

Data Visualization: Kamon focuses on real-time metrics and tends to be more lightweight in terms of data visualization compared to Kibana, which provides a more robust and visually appealing data visualization platform with interactive charts, graphs, and dashboards.
Data Aggregation: Kibana offers advanced data aggregation capabilities, allowing users to aggregate, filter, and analyze data from various sources with ease. On the other hand, Kamon provides basic data aggregation features without the advanced capabilities found in Kibana.
Integration: Kibana integrates seamlessly with Elasticsearch, providing users with a powerful monitoring and analysis solution within the Elastic Stack. In contrast, Kamon can be integrated with various data stores but may require additional configuration and setup compared to the seamless integration offered by Kibana.
Community Support: Kibana has a larger and more active community, providing users with a wealth of resources, plugins, and support compared to Kamon, which may have a smaller community and limited resources available for users.
Alerting and Monitoring: Kibana offers robust alerting and monitoring features, allowing users to set up custom alerts based on specific criteria and monitor system health in real time. Kamon, while capable of basic monitoring, may lack the advanced alerting capabilities found in Kibana.
Ease of Use: Kibana is known for its user-friendly interface and intuitive design, making it easy for users to navigate and use its features. Kamon, while functional, may not offer the same level of ease of use and may require a steeper learning curve for users.

In Summary, Kamon and Kibana differ in data visualization, data aggregation, integration, community support, alerting and monitoring, and ease of use, making them suitable for different monitoring and analysis needs.

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CLI (Node.js)

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Advice on Kibana, Kamon

matteo1989it

Jun 26, 2019

Reviewon

Kibana

Grafana

Elasticsearch

I use both Kibana and Grafana on my workplace: Kibana for logging and Grafana for monitoring. Since you already work with Elasticsearch, I think Kibana is the safest choice in terms of ease of use and variety of messages it can manage, while Grafana has still (in my opinion) a strong link to metrics

757k views757k

Comments

StackShare

Jun 25, 2019

Needs advice

From a StackShare Community member: “We need better analytics & insights into our Elasticsearch cluster. Grafana, which ships with advanced support for Elasticsearch, looks great but isn’t officially supported/endorsed by Elastic. Kibana, on the other hand, is made and supported by Elastic. I’m wondering what people suggest in this situation."

663k views663k

Comments

abrahamfathman

Jun 26, 2019

Reviewon

Kibana

Splunk

Grafana

I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.

2.29M views2.29M

Comments

Detailed Comparison

Kibana	Kamon
Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.	Kamon helps developers find and fix performance issues in Akka and Play Framework microservices. Kamon Telemetry is a battle tested free and open-source instrumentation library and Kamon APM is an easy-to-use APM with pre-built dashboards.
Flexible analytics and visualization platform;Real-time summary and charting of streaming data;Intuitive interface for a variety of users;Instant sharing and embedding of dashboards	Pre built integrations for Akka/Play/JVM/JDBC; Distributed tracing; Services Map; Separate test and production environments; Host monitoring; Custom dashboards; Alerting
Statistics
GitHub Stars 20.8K	GitHub Stars -
GitHub Forks 8.5K	GitHub Forks -
Stacks 20.6K	Stacks 7
Followers 16.4K	Followers 12
Votes 262	Votes 3
Pros & Cons
Pros 88 Easy to setup 65 Free 45 Can search text 21 Has pie chart 13 X-axis is not restricted to timestamp Cons 7 Unintuituve 4 Elasticsearch is huge 4 Works on top of elastic only 3 Hardweight UI	Pros 1 Affordable for small teams or startups 1 Easy set-up 1 Generous free plan (up to 5 services, no time limit)
Integrations
Logstash Elasticsearch Beats	No integrations available

What are some alternatives to Kibana, Kamon?

Grafana

Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.

Prometheus

Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

Nagios

Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.

Netdata

Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

Zabbix

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

Sensu

Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.

Graphite

Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand

Lumigo

Lumigo is an observability platform built for developers, unifying distributed tracing with payload data, log management, and real-time metrics to help you deeply understand and troubleshoot your systems.

StatsD

It is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).

Jaeger

Jaeger, a Distributed Tracing System

Related Comparisons

Kamon vs Kibana: What are the differences?

Introduction: Kamon and Kibana are both tools used for monitoring and analyzing applications, but they have key differences that set them apart.

Data Visualization: Kamon focuses on real-time metrics and tends to be more lightweight in terms of data visualization compared to Kibana, which provides a more robust and visually appealing data visualization platform with interactive charts, graphs, and dashboards.
Data Aggregation: Kibana offers advanced data aggregation capabilities, allowing users to aggregate, filter, and analyze data from various sources with ease. On the other hand, Kamon provides basic data aggregation features without the advanced capabilities found in Kibana.
Integration: Kibana integrates seamlessly with Elasticsearch, providing users with a powerful monitoring and analysis solution within the Elastic Stack. In contrast, Kamon can be integrated with various data stores but may require additional configuration and setup compared to the seamless integration offered by Kibana.
Community Support: Kibana has a larger and more active community, providing users with a wealth of resources, plugins, and support compared to Kamon, which may have a smaller community and limited resources available for users.
Alerting and Monitoring: Kibana offers robust alerting and monitoring features, allowing users to set up custom alerts based on specific criteria and monitor system health in real time. Kamon, while capable of basic monitoring, may lack the advanced alerting capabilities found in Kibana.
Ease of Use: Kibana is known for its user-friendly interface and intuitive design, making it easy for users to navigate and use its features. Kamon, while functional, may not offer the same level of ease of use and may require a steeper learning curve for users.

Kamon vs Kibana

Overview