Datadog vs. Grafana Cloud

Compare Datadog vs. Grafana Cloud for Observability. We want you to choose the most suitable tool for your use case, even if it’s not us.

As cloud-native environments continue to grow in complexity, observability has become essential for ensuring the reliability, performance, and scalability of modern applications. From monitoring infrastructure health, enabling deep visibility into distributed systems, or getting real-time insights into reasoning paths, token usage of LLM Agentic applications. However, traditional vendors sliced visibility into separate products (APM, Log Management, Infrastructure Monitoring, LLM Observability) and priced them in ways that forced tradeoffs making it important for team to choosing the right observability platform is critical to operational success.

Datadog and Grafana Cloud each bring unique strengths to observability, with distinct capabilities and trade-offs. The best fit depends on your organization’s priorities—whether that’s cost efficiency, deployment flexibility, developer experience, or ecosystem integrations.

The right choice depends on your priorities: cost, control, scale, and flexibility. In the following sections, we’ll compare both platforms to help you determine which best fits your needs, even if the answer isn’t us.

Datadog vs. Grafana Cloud at a glance

Datadog
Grafana Cloud
BYOC (Data Residency, Compliance, Security)
On Prem (Data Residency, Compliance, Security)
With Grafana OSS only
Correlation between logs, metrics, traces
Kubernetes native
Limited
Full HTTP Payloads of Request as well as response including headers
(available via USM+ additional cost)
Smart Sampling

Datadog vs. Grafana Cloud at a glance

Datadog
Grafana Cloud
RBAC for user roles
RBAC for Pages
RBAC for Actions
Fine-grain access control to data/resources (namespace setup support) to provide access to specific teams or by data type (MELT)
In preview

Datadog vs. Grafana Cloud at a glance

Datadog
Grafana Cloud
All data types included in standard plan
APM, Logs, LLM, RUM, Infrastructure Monitoring all sold separately
APM, Logs, LLM, RUM, Infrastructure Monitoring all sold separately
No Ingestion based pricing
Additional costs based on retention
Costs increase when retention policies applied
Costs increase when retention policies applied
Additional costs for indexed data
Additional price bands for hot/cold storage
Additional price bands for hot/cold storage
Out of the box LLM Observability (tokens, hallucinations, drift)
(Requires the installation of an additional agent)
No Additional Cost
(Manual instrumentation is possible and charges will apply)
RUM
No Additional Cost
(Additional charges are incurred by sessions)
(Additional charges are incurred by events + sessions)

Datadog overview

Datadog is a SaaS-based monitoring, security, and analytics platform for developers, IT operations teams, security engineers, and business users. It integrates infrastructure monitoring, application performance monitoring (APM), log management, user experience monitoring, and cloud security into a modular system where organizations can choose the components they need. The platform provides real-time observability across the entire technology stack, helping teams monitor systems, detect and resolve issues, secure applications and infrastructure, and analyze user behavior and business metrics. Datadog is used by organizations of different sizes and industries to support cloud migration, enable collaboration across technical and business teams, shorten time to market for applications, and reduce time to problem resolution.

Grafana Cloud overview

Grafana Cloud is a fully managed observability platform that brings together metrics, logs, and traces using open-source projects such as Grafana, Prometheus, Loki, Tempo, and Mimir. It provides dashboards, alerting, and analytics in a single hosted service, removing the need for teams to deploy and manage their own observability stack. The platform supports infrastructure, application, and Kubernetes monitoring, with prebuilt dashboards and integrations for more than 100 external data sources. Additional capabilities include performance testing with Grafana k6, incident management with Grafana Incident and Grafana OnCall, and AI-powered features like anomaly detection and metric forecasting. Grafana Cloud is used by teams that want to standardize on open-source observability tools while offloading the operational overhead of running them at scale.

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