Azure Monitor wins on cost, Azure-native simplicity, and KQL log analytics; Datadog wins on UX polish, APM, and multi-cloud coverage. Most teams run both.
| Feature | Azure Monitor | Datadog |
|---|---|---|
| Best For | Azure-native monitoring with KQL log analytics | Multi-cloud unified observability |
| Pricing | Billing is primarily based on the volume of data ingested into Azure Monitor. Use capacity reservation tiers to save up to 36 percent on data ingestion costs as compared to pay-as-you-go pricing. Some functionalities have additional charges. | Free tier available, paid plans start at $0.75 per host per month, additional costs based on usage and features |
| Cloud coverage | Azure + hybrid via Azure Arc | AWS, Azure, GCP, hybrid, on-prem |
| Azure service integration | Zero-config automatic | Integration installed per service |
| Feature | Azure Monitor | Datadog |
|---|---|---|
| Cloud & Infrastructure | ||
| Cloud coverage | Azure + hybrid via Azure Arc | AWS, Azure, GCP, hybrid, on-prem |
| Azure service integration | Zero-config automatic | Integration installed per service |
| Agent deployment | Azure Monitor Agent for custom/non-Azure hosts | Datadog Agent on Linux/Windows/K8s/serverless |
| Access control | Azure AD native, RBAC | Datadog users + SAML SSO on paid tiers |
| Observability Capabilities | ||
| Log query language | KQL (Kusto Query Language) | Datadog query language |
| APM and tracing | Application Insights (integrated) | Unified Datadog APM |
| Real user monitoring | Application Insights basic RUM | Native Datadog RUM |
| Synthetic monitoring | Availability tests in App Insights | Full synthetics suite with global locations |
| Pricing & SIEM | ||
| Billing model | Per GB ingested + retention | Per host + usage add-ons per SKU |
| Free tier | 5 GB/month Log Analytics, 31-day retention | 5 hosts, 1-day retention |
| SIEM integration | Microsoft Sentinel (same workspace) | Datadog Cloud SIEM (separate SKU) |
| Capacity savings | Capacity reservations save up to 36% | Volume discounts on Enterprise contracts |
Cloud coverage
Azure service integration
Agent deployment
Access control
Log query language
APM and tracing
Real user monitoring
Synthetic monitoring
Billing model
Free tier
SIEM integration
Capacity savings
Azure Monitor wins on cost, Azure-native simplicity, and KQL log analytics; Datadog wins on UX polish, APM, and multi-cloud coverage. Most teams run both.
Choose Azure Monitor if:
Choose Azure Monitor when your workload is Azure-only and cost discipline matters more than dashboard polish
Choose Datadog if:
Choose Datadog when you run multi-cloud or need polished APM, RUM, and synthetics in one product
Choose Azure Monitor if:
Use both together: Azure Monitor for collection, Datadog on top via Diagnostic Settings plus Event Hubs
This verdict is based on general use cases. Your specific requirements, existing tech stack, and team expertise should guide your final decision.
Yes, and many teams do. The common pattern is Azure Monitor Diagnostic Settings forwarding Azure resource telemetry to Datadog via Event Hubs. This gives you Datadog dashboards on top of Azure Monitor's zero-config Azure collection and avoids deploying the Datadog Agent to every Azure VM.
Yes, via Application Insights. It auto-instruments major .NET workloads and provides SDK-based instrumentation for other languages. It is solid for backend services; Datadog APM is stronger for polished end-to-end tracing but Application Insights is competitive and cheaper for Azure-native workloads.
Azure Monitor is almost always cheaper for Azure-only workloads, often by a factor of 5-10x. Datadog's per-host pricing plus per-feature SKUs stacks up quickly. However, if Datadog replaces 2-3 other tools, the consolidated total can come out cheaper.
Yes, though it's usually additive rather than replacement. You install the Datadog Agent on your Azure VMs or forward via Diagnostic Settings plus Event Hubs, replicate dashboards and alerts, run parallel for 2-4 weeks to validate alarm parity, then decommission Azure Monitor alerts.
Azure Monitor's KQL is more expressive for complex log analytics queries. Datadog Logs has better search UX and cross-correlation. For heavy log analytics workloads especially security-driven, Microsoft Sentinel on the same Log Analytics workspace is often the strongest answer.