Datadog vs. Chronosphere

Compare Datadog vs. Chronosphere 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 Chronosphere 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. Chronosphere at a glance

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

Datadog vs. Chronosphere at a glance

Datadog
Chronosphere
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. Chronosphere at a glance

Datadog
Chronosphere
All data types included in standard plan
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
RUM
No Additional Cost
(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.

Chronosphere overview

Chronosphere is a cloud-native observability platform built to help engineering teams manage the scale, complexity, and cost of modern applications. It provides visibility across infrastructure, applications, and business metrics, giving DevOps and SRE teams the ability to detect and resolve issues before they impact users. By centralizing telemetry data and offering tools like Chronosphere Lens, it helps organizations reduce noise, improve reliability, and boost developer productivity.

Purpose-built for the demands of cloud-native environments, Chronosphere helps customers lower the cost of ingesting telemetry by giving user access to smart tools to optimize which data they keep and where they store it. Fluent Bit–based telemetry pipeline, and focus on flexibility help teams control data growth without sacrificing insight.

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