Buying snapshot
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| Decision point | What Datadog states |
|---|---|
How it runs | Hosted service. In containerized environments the Datadog agent runs in a container on each host and monitors the host and all its running containers. |
Agent license | Agent user space components: Apache License 2.0. BPF code: GPL 2.0. The license covers the agent, not the hosted platform. |
Billable host | Any physical or virtual OS instance you monitor: a server, VM, Kubernetes node or Azure App Service Plan instance. |
Billing terms | Annual and monthly plans are available, and Datadog says it can customize billing plans. |
Trying it | Free trial offered, including a Start Free Trial option on the Feature Flags plan card. |
Security and compliance | TCP/SSL Strict Transport Security, agent-level scrubbing and SOC 2 compliance. |
Integrations and API | All listed integrations are supported by Datadog. A RESTful HTTP API gives full data access. |
Our take
Choose Datadog if you want metrics, logs, traces and security signals in one hosted service and you can assign someone to track each product's meter. If you need one fixed monitoring price, model every product you plan to enable before you commit.
Evaluate Datadog
Popular comparisons
See 20 Datadog comparisons
Where it stands out
Signals in one place. Datadog lets you move between logs, metrics and request traces and see log data with automated tagging and correlation. That shortens incident work that crosses hosts, services and logs.
Agent you can inspect. Datadog says its agent is open source, so it can be reviewed against your security requirements before rollout.
Two log storage tiers. Datadog suggests Standard Indexing for real-time troubleshooting and Flex Logs for ad-hoc, historical analysis, so not every log needs the same treatment.
Flexible alerting. Alerts work on any metric for a single host or a whole cluster, with multiple trigger conditions and notifications via e-mail, PagerDuty, Slack and other channels.
Products bought on their own. App Builder and Feature Flags do not require other Datadog products. Feature Flags is built on the OpenFeature standard, which Datadog says simplifies migration from other providers.
Product screenshot
Trade-offs to weigh
Overage on committed log volume. On a log commitment, volume above the commitment is billed at +50% of the annual price. Size the commitment against busy months, not average ones.
Container counts drive the bill. Depending on your plan, 4 containers per host license are free; extra containers are billed per container per hour. Dense Kubernetes nodes need a container estimate, not just a host count.
One APM plan across all hosts. You cannot mix APM Enterprise on some hosts with standalone products on the rest. APM-only customers can add Continuous Profiler or Data Streams Monitoring on part of their hosts.
No cross-account log forwarding. Forwarding logs from one Datadog account to another is not supported. Plan account boundaries before you split teams or environments.
Region gaps. Feature Flags is available in US-, EU- and APAC-hosted accounts but not in GovCloud.
Pricing and plan conditions
Datadog prices each product on its own unit: hosts, containers, LLM spans, flag configuration requests, published apps or log volume. Most products show an annual rate and a separate monthly or on-demand rate. Datadog for Startups offers one year of free Datadog Pro to accepted applicants. The table shows selected products with published rates.
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| Product or plan | Published price | What it includes |
|---|---|---|
Infrastructure Free | $0 | Core collection and visualization features, 1-day metric retention, up to 5 hosts |
Infrastructure Pro | $15 per host per month billed annually, or $18 on-demand | 1,000+ integrations, out-of-the-box dashboards, 15-month metric retention |
Infrastructure Enterprise | $23 per host per month billed annually, or $27 on-demand | Advanced features and administrative controls: machine learning-based alerts, Live Processes, Governance Console |
Agent Observability Free | $0 per month | Up to 40K LLM spans per month, 15-day trace retention, unlimited context and evals, full feature access |
Agent Observability Pro | Starting at $160 per month (annual pricing shown; on-demand and M2M options available) | 100K LLM spans per month included; additional spans $3.50 per 10K LLM spans. Billed on LLM spans only, not tool, workflow or retrieval spans. |
Feature Flags, 1M-10M MFCRs | Per 1M MFCRs: $55 annual, $89 monthly, $100 on-demand | Monthly Flag Configuration Requests (MFCRs). Usage below 1 million MFCRs is included at no cost. |
Feature Flags, 10M+ MFCRs | Per 1M MFCRs: $45 annual, $73 monthly, $92 on-demand | The billing FAQ lists these rates; the plan card says Contact Us for Pricing for 10M+ MFCRs. |
Continuous Profiler (standalone) | $19 per profiled host per month with an annual commitment; $23 per profiled host per month or $0.004 per hour on month-to-month and on-demand plans | Supports Java, .NET, Go, Python, Ruby, Node.js and PHP; C, C++ and Rust in beta. |
App Builder | $35 per published app per month billed annually, or $51 on-demand | Free to start using; an app becomes paid once it is published. Multi-Year/Volume discounts available. |
Prepaid containers | $1 per container per month | Prepaid alternative to hourly billing for containers beyond the per-host allotment |
Log forwarding | Starting at $0.25 per GB outbound per destination | Applies to destinations such as an external SIEM or BI vendor. Forwarding to S3 Archives, GCP Storage and Azure Storage is included with $0.10 per ingested GB. |
Flex Logs | Metered hourly per million events stored | Each million events stored is billed for a minimum of 30 days, or a minimum of $0.05 |
Public signals
About these signals
Verified factual signals from public sources. They indicate observable activity or interest, not total adoption, product quality, or cost.
3.3k GitHub commits 90d3.8k GitHub stars0 vulnerabilities across 2 packagesOpenSSF score 4.5/10
See all signals from 10 sources
PyPI · datadog@0.56.0 · npm · dd-trace@6.21.0
Alternatives to Datadog
The reviewed substitutes for Datadog among the observability platforms, and what would make each one the better answer.
Direct alternatives
Reviewed substitutes: products bought for the same job, where a team picks one.
- New Relic
- **Datadog** is the most direct competitor to New Relic, offering a unified platform that spans APM, infrastructure monitoring, log management, real user monitoring, synthetic testing, and security monitoring. Choose Datadog if you need the broadest integration ecosystem and want AI-powered anomaly detection across all telemetry types without manual configuration.
- Better Stack
- Datadog and Better Stack both monitor production systems, collecting logs and metrics and alerting the team when something breaks. Datadog is a broad platform covering infrastructure, APM, logs and security, while Better Stack focuses on logs, uptime checks, incident alerts and status pages in one product.Applies to: Choosing the observability backend that will receive OpenTelemetry data and carry on-call.
- Coralogix
- Datadog and Coralogix both ingest logs, metrics and traces, alert on them and support debugging. Datadog is a broad platform for infrastructure, APM and security, while Coralogix analyses data in stream as it arrives and controls what is stored, which keeps high log volumes affordable.Applies to: Choosing the observability backend that will receive OpenTelemetry data and carry on-call.
- Honeycomb
- To find out why a distributed system is slow or failing, a team can use Datadog or Honeycomb. Datadog is a broad SaaS platform covering infrastructure, application and log monitoring, while Honeycomb is built for debugging, with fast queries over rich trace and event data and support for LLM observability.Applies to: Choosing between these two for the apm observability decision.
Other approaches
A different approach to the same problem. Each substitutes only for the workload named beside it.
- Dynatrace
- Dynatrace is preferred over Datadog for full-stack monitoring workloads that need observability, automation, and application security under one annual platform commitment. **Dynatrace** combines observability, AI, automation, application security, and business-outcome framing in one platform.
- Elastic Observability
- Elastic Observability is an alternative to Datadog for teams prioritizing open-source-based observability and paid monthly plans. **Elastic Observability** is an open-source-based observability offering positioned around storing more data, troubleshooting faster, and using agentic AI for investigation.Applies to: for teams that want an observability platform explicitly built on open source and value control over their data approach.
- Grafana Cloud
- Same four signals, one managed open-source, one proprietary usage-based.Applies to: Managed metrics, logs and traces for a production estate.
- Observe
- Observe is a modern observability platform built on a streaming data lake, for faster search and correlation at lower cost.Applies to: cloud-scale infrastructure, application, and log monitoring workloads
- Splunk
- Splunk and Datadog both collect, search and alert on logs and monitoring data, and teams move those workloads from one to the other. Splunk indexes machine data into a searchable repository and is strongest at log search and analysis; Datadog is a SaaS monitoring service where logs sit beside infrastructure metrics and application performance data.Applies to: Storing, searching and alerting on logs and monitoring data. Splunk stands in where deep log search and analysis lead; Datadog stands in where infrastructure and application monitoring lead and logs come along.
- AppDynamics
- Both are full-stack APM and observability platforms; Datadog is usage-based SaaS where AppDynamics is an enterprise licence.Applies to: Monitoring a production application estate across cloud and on-prem hosts.
- Google Cloud Operations
- Datadog and Google Cloud Operations both provide monitoring, logging and alerting for workloads on Google Cloud. Google Cloud Operations is Google's native suite and needs no separate setup for Google services; Datadog is an independent platform that brings the same view to every cloud a company uses.Applies to: Whether the cloud provider's own monitoring is enough, or a third-party platform is needed.
- Uptrace
- Datadog is preferred over Uptrace for cloud-scale monitoring workloads where teams specifically want a platform spanning infrastructure, applications, and logs. **Datadog** is a cloud-scale monitoring and observability platform for infrastructure, applications, and logs. It is designed for IT, Dev, and Ops teams that need to turn high volumes of operational data into actionable insight at scale.