Kibana vs Loggly: What are the differences?

Introduction

Here, we will focus on the key differences between Kibana and Loggly as two popular log management and analytics tools.

1. Deployment and Hosting: Kibana is an open-source tool developed by Elastic and can be self-hosted or hosted on platforms like Elastic Cloud. On the other hand, Loggly is a cloud-based log management solution, where the entire infrastructure and hosting are handled by Loggly.

2. Search and Querying: Kibana provides a powerful search and querying interface with its Elasticsearch integration. It offers a wide range of advanced search capabilities, including full-text search, filtering, and aggregations. Loggly also offers searching and querying features, but it focuses more on speed and simplicity, providing pre-built search filters and the ability to construct queries using standard search syntax.

3. Visualization and Dashboards: Kibana is well-known for its rich visualization features. It offers an extensive collection of visualization options, including line charts, bar charts, maps, and more. With its drag-and-drop dashboard builder, users can create interactive and personalized dashboards. Loggly, however, has a more limited set of visualization capabilities. It offers basic charting and graphing options, but it doesn't have the same level of customization or variety as Kibana.

4. Alerting and Monitoring: Kibana lacks built-in alerting and monitoring features by default. It relies on external integrations or plugins, such as Elasticsearch Watcher or third-party tools, to enable alerting and monitoring. On the other hand, Loggly provides built-in alerting functionality, allowing users to set up alerts based on specific log events or patterns, and receive notifications via various channels like email or Slack.

5. Log Ingestion and Parsing: Kibana relies on Elasticsearch for log ingestion, and it supports different log file formats. By using Logstash, users can preprocess logs before indexing them into Elasticsearch. Loggly, on the other hand, offers various ingestion methods, including bulk upload, syslog, log shippers, and log routing. It also provides automatic parsing and extraction of log events, making it easier to analyze and search through log data without much configuration.

6. Ease of Use and Learning Curve: Kibana has a steeper learning curve compared to Loggly, primarily due to its advanced features and flexibility. It requires some knowledge of Elasticsearch and the query language. Loggly, on the other hand, has a more user-friendly interface and offers a simpler setup process, making it easier for non-technical users or those new to log management to get started quickly.

In Summary, Kibana and Loggly have notable differences in deployment, search capabilities, visualization, alerting, log ingestion, and ease of use. These variations make them suitable for different use cases and user preferences.