Kibana vs Shinken: What are the differences?

Introduction

Kibana and Shinken are both popular tools used in the field of data analysis and monitoring, but they have key differences that set them apart. Here are some of the main differences between Kibana and Shinken.

1. Purpose: Kibana is primarily used for data visualization and analytics, specifically for analyzing data stored in Elasticsearch. On the other hand, Shinken is a monitoring solution designed to monitor complex IT infrastructures and provide alerts in case of any issues or failures. While Kibana focuses on visualizing data, Shinken focuses on monitoring the health and performance of IT systems.

2. Technology Stack: Kibana is typically used in conjunction with the ELK stack (Elasticsearch, Logstash, Kibana), where Elasticsearch is used for data storage and retrieval, Logstash for data processing, and Kibana for visualization. In contrast, Shinken is a standalone monitoring tool that can be integrated with various data sources such as Nagios, Icinga, and Zabbix. The technology stack for Shinken is more diverse and flexible compared to the more streamlined ELK stack used by Kibana.

3. Scalability: Kibana is known for its scalability in terms of handling large volumes of data and supporting real-time visualization of the data. It can easily scale horizontally by adding more nodes to the Elasticsearch cluster. On the other hand, Shinken is also scalable but more focused on scaling in terms of monitoring a large number of devices and services. Shinken is designed to handle complex IT infrastructures with ease and can scale to monitor thousands of devices.

4. User Interface: Kibana provides a user-friendly interface with powerful visualization tools such as charts, graphs, and dashboards for analyzing data. It offers a more intuitive and interactive experience for users to explore and interpret data effectively. In contrast, Shinken has a more utilitarian interface focused on monitoring the status and performance of IT systems. It provides detailed information on alerts, notifications, and service checks in a straightforward manner.

5. Community Support: Kibana has a large and active community of users and developers who contribute to its development and provide support through forums, documentation, and tutorials. This makes it easier for users to find resources and solutions to their problems. Shinken, on the other hand, has a smaller community compared to Kibana but is still well-supported by a dedicated user base and developers who are actively involved in improving the tool and addressing issues.

6. Customization: Kibana offers a high level of customization options for visualization and dashboard creation, allowing users to tailor their data analysis and presentation to their specific requirements. Users can create custom visualizations, dashboards, and reports to suit their data analysis needs. Shinken also allows for customization, but its focus is more on configuring monitoring checks, alerts, and notification settings to meet the specific monitoring requirements of IT systems.

In Summary, Kibana is a data visualization and analytics tool that is part of the ELK stack, while Shinken is a standalone monitoring solution designed for monitoring complex IT infrastructures.