Best Log Analysis Software
Log analysis software helps to document application log files for records and analytics. This type of software provides tools to increase the collection of logs and to supply centralized databases to store the data. From there, log analysis tools provide analytics components to identify the cause and impact of events. Monitoring features also form a large component of log analysis. These features help detect, predict, and prevent future anomalies. Companies use this data to better understand performance failures, remediate them, and learn how to prevent them in the future. As a result, application performance and reliability is improved. Some application performance monitoring (APM) software software and container monitoring software software have log analytics features, but typically do not focus on log management specifically.
To qualify for inclusion in the Log Analysis category, a product must:
- Document operations and authentication events
- Store logs in a centralized location
- Provide analytics features to identify causation and event prediction
- Assist in mapping, tagging, and classifying logs
Log Analysis Software Grid® Overview
The best Log Analysis Software products are determined by customer satisfaction (based on user reviews) and scale (based on market share, vendor size, and social impact) and placed into four categories on the Grid®:
- Products in the Leader quadrant are rated highly by G2 Crowd users and have substantial Market Presence scores. Leaders include: Splunk Enterprise
- High Performers are highly rated by their users, but have not yet achieved the market share and scale of the Leaders. High Performers include: Logz.io and Scalyr
- Contenders have significant Market Presence and resources, but have received below average user Satisfaction ratings or have not yet received a sufficient number of reviews to validate the solution. Contenders include: Datadog
- Niche solutions do not have the Market Presence of the Leaders. They may have been rated positively on customer Satisfaction, but have not yet received enough reviews to validate them.