Log Analysis Software Resources

What is the difference between Coralogix and other hosted machine data services

Looking at data on the Log Analysis category page, several platforms stand out for teams that need strong security threat detection in logs. These solutions help organizations detect suspicious activity, correlate signals across environments, and investigate incidents faster through alerting, anomaly detection, and security-focused analytics. See below for my top platform list:

Panther – Security-first log analysis built for detection engineering. Strong for cloud SIEM-style threat detection, alerting, and rule-based detections across AWS, GCP, and SaaS logs.

Datadog – Strong for threat detection when you want security monitoring integrated with observability. Useful for correlating log events with infrastructure and application behavior to detect anomalies and suspicious patterns.

Sumo Logic – Great for centralized security analytics at scale, with strong log search, dashboards, and alerting that supports SOC workflows and threat investigation.

Dynatrace – Best for enterprises that want AI-driven correlation across logs, metrics, and traces to surface security anomalies alongside operational issues in complex cloud environments.

ManageEngine Log360 – Strong for compliance-driven security monitoring and log auditing. A good fit when SIEM-style tracking, reporting, and alerting are required for IT security and governance teams.

For those using log analysis for security: where have you seen the biggest ROI—faster detection, better correlation, reduced false positives, or easier investigations—and which platform has performed best in real-world threat detection?

Hey G2 community! I’m diving into Log Analysis Software that doesn’t just store logs, but also integrates cleanly with cloud monitoring systems—APM, infrastructure monitoring, metrics, traces, and alerting workflows. Based on the G2 Log Analysis category, here are a few strong contenders:

Datadog: Datadog is a strong fit because logs, metrics, traces, and infrastructure monitoring all live in one unified platform. It’s ideal when teams want end-to-end observability with correlation between log events and performance issues across cloud services.

New Relic: New Relic is built for full-stack observability and integrates logs tightly with APM and infrastructure monitoring. It’s especially useful for teams that want logs to be searchable and contextualized directly alongside application performance and service health.

Dynatrace: Dynatrace is strong for enterprises that want deep cloud monitoring with automatic correlation across metrics, traces, and logs. It’s a good choice when teams need AI-assisted root-cause analysis and unified monitoring across large, complex environments.

Cloud monitoring + log integration usually comes down to three things: native correlation across logs/metrics/traces, centralized dashboards and alerting, and fast root-cause workflows across cloud services—areas where Datadog, New Relic, and Dynatrace tend to stand out.