groundcover vs. Datadog

Compare groundcover vs. Datadog 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.

groundcover and Datadog 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.

groundcover vs. Datadog at a glance

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

groundcover vs. Datadog at a glance

groundcover
Datadog
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

groundcover vs. Datadog at a glance

groundcover
Datadog
All data types included in standard plan
APM, Logs, LLM, RUM, Infrastructure Monitoring all sold separately
No Ingestion based pricing
No ingestion fees (Ingestion depends on own storage)
Additional costs based on retention
No additional retention pricing. Keep as much as you want
Costs increase when retention policies applied
Additional costs for indexed data
All data is indexed at no additional costs
Additional price bands for hot/cold storage
Out of the box LLM Observability (tokens, hallucinations, drift)
(Requires the installation of an additional agent)
LLM Observability: No Additional Cost
Real User Monitoring (RUM)
RUM: No Additional Cost
(Additional charges are incurred by events + sessions)

groundcover overview

groundcover is a full-stack observability platform that goes beyond the traditional SaaS limitations by giving teams complete control of their telemetry in their own cloud. It delivers APM, log management, infrastructure monitoring, LLM observability, and Real User Monitoring (RUM) in a single, unified solution — all with zero instrumentation, powered by eBPF.

With a BYOC (Bring Your Own Cloud) model, groundcover eliminates SaaS markups and data tradeoffs, providing complete visibility, infinite retention, and flat, predictable pricing. From infrastructure to applications to Agentic Application workloads, groundcover captures every signal — without sampling or rate limits — and keeps it private and secure inside your VPC. Whether running in the cloud, on-prem, or in regulated environments, groundcover gives engineering teams operational simplicity, cost clarity, and observability that just works, without compromise.

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.

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