What are the key differences between Datadog and Application Insights?

Compare Datadog and Application Insights side by side on Lunoo to see detailed feature differences, AI scores, and expert analysis.

How are Datadog and Application Insights scored?

Datadog has an AI score of 8.62/10 and Application Insights has an AI score of 9.15/10. Scores are based on category fit, feature coverage, pricing signals, public reception, and recency.

Datadog vs Application Insights 2026 - Compared

Datadog

Application Insights

WINNER Application Insights

Application Insights edges ahead with a score of 9.2/10 compared to 8.6/10 for Datadog. While both are highly rated in t...

Datadog

8.62 Great

Observability Platform Get Datadog open_in_new

emoji_events WINNER

Application Insights

9.15 Excellent

Azure Monitor Get Application Insights open_in_new

Datadog From $15/user/month Free plan available

payments

Application Insights Pricing not available

psychology AI Verdict

Application Insights edges ahead with a score of 9.2/10 compared to 8.6/10 for Datadog. While both are highly rated in their respective fields, Application Insights demonstrates a slight advantage in our AI ranking criteria. A detailed AI-powered analysis is being prepared for this comparison.

emoji_events Winner: Application Insights

verified Confidence: Low

Ready to decide? Get Application Insights arrow_forward

description Overview

Datadog

Datadog is a leading observability and security platform for cloud-scale applications. It provides full-stack monitoring, including infrastructure, logs, application performance (APM), and user experience. By aggregating data from across the entire tech stack, Datadog helps engineering teams identify and resolve performance bottlenecks and security vulnerabilities in real-time. Its ability to visu...

Application Insights

Application Insights focuses on what happens inside an application when it receives work. With suitable instrumentation, it collects telemetry about requests and dependencies, helping developers connect errors with the operations that produced them. Distributed tracing can follow a request through several services, making it useful when a slowdown is difficult to locate in a microservices applicat...