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Dynatrace Pricing & Plans 2026

Complete pricing guide for Dynatrace. Compare all plans, analyze costs, and find the perfect tier for your needs.

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Still deciding? Read our full verdict on whether Dynatrace is worth it →

🆓Free Tier Available
💎5 Paid Plans
⚡No Setup Fees

Choose Your Plan

Full-Stack Monitoring

From $0.04/hour per 8 GiB host

mo

  • ✓OneAgent auto-instrumentation
  • ✓APM and distributed tracing (PurePath)
  • ✓Infrastructure and Kubernetes monitoring
  • ✓Davis AI causal root-cause analysis
  • ✓Smartscape topology mapping
Start Free Trial →

Infrastructure Monitoring

From $0.01/hour per host

mo

  • ✓Host, container, and process monitoring
  • ✓Network and process metrics
  • ✓Cloud platform integrations (AWS, Azure, GCP)
  • ✓Davis AI anomaly detection
  • ✓Log ingestion (priced separately)
Start Free Trial →
Most Popular

Log Management & Analytics

From $0.0001 per GiB scanned (Grail)

mo

  • ✓Grail data lakehouse storage
  • ✓Index-free log ingestion
  • ✓DQL query language
  • ✓Long-term retention
  • ✓Davis AI on log data
Start Free Trial →

Application Security

From $0.018/hour per 8 GiB host

mo

  • ✓Runtime vulnerability analytics
  • ✓Real exploit-risk prioritization
  • ✓Runtime application protection
  • ✓Attack detection and blocking
  • ✓DevSecOps workflow automation
Start Free Trial →

Digital Experience Monitoring

Priced per DEM unit (RUM + synthetic)

mo

  • ✓Real user monitoring (RUM)
  • ✓Session replay
  • ✓Synthetic browser and HTTP monitors
  • ✓Mobile app monitoring
  • ✓Business analytics on user sessions
Start Free Trial →

Pricing sourced from Dynatrace · Last verified March 2026

Feature Comparison

FeaturesFull-Stack MonitoringInfrastructure MonitoringLog Management & AnalyticsApplication SecurityDigital Experience Monitoring
OneAgent auto-instrumentation✓✓✓✓✓
APM and distributed tracing (PurePath)✓✓✓✓✓
Infrastructure and Kubernetes monitoring✓✓✓✓✓
Davis AI causal root-cause analysis✓✓✓✓✓
Smartscape topology mapping✓✓✓✓✓
Host, container, and process monitoring—✓✓✓✓
Network and process metrics—✓✓✓✓
Cloud platform integrations (AWS, Azure, GCP)—✓✓✓✓
Davis AI anomaly detection—✓✓✓✓
Log ingestion (priced separately)—✓✓✓✓
Grail data lakehouse storage——✓✓✓
Index-free log ingestion——✓✓✓
DQL query language——✓✓✓
Long-term retention——✓✓✓
Davis AI on log data——✓✓✓
Runtime vulnerability analytics———✓✓
Real exploit-risk prioritization———✓✓
Runtime application protection———✓✓
Attack detection and blocking———✓✓
DevSecOps workflow automation———✓✓
Real user monitoring (RUM)————✓
Session replay————✓
Synthetic browser and HTTP monitors————✓
Mobile app monitoring————✓
Business analytics on user sessions————✓

Is Dynatrace Worth It?

✅ Why Choose Dynatrace

  • • Davis AI provides deterministic, causal root-cause analysis rather than just statistical correlation, reducing alert noise and accelerating MTTR in complex distributed systems
  • • Single OneAgent deployment automatically discovers and instruments hosts, containers, services, and dependencies — eliminating most manual instrumentation work that competing tools require
  • • Grail data lakehouse stores logs, metrics, traces, and events without indexing, enabling fast DQL queries across petabyte-scale data without pre-aggregation trade-offs
  • • Unified platform consolidates APM, infrastructure, logs, RUM, synthetic, and runtime security — reducing the need to license and integrate multiple separate tools
  • • Strong support for hybrid and multi-cloud environments including AWS, Azure, GCP, Kubernetes, OpenShift, SAP, and mainframe — making it well-suited to large enterprises with heterogeneous stacks
  • • Publicly traded company (NYSE:DT) with 20+ years of operating history and enterprise-grade SLAs, security certifications, and 24/7 support phone lines (+1-844-900-3962 for technical support)

⚠️ Consider This

  • • Pricing is widely regarded as among the highest in the observability category, with consumption-based costs that can become unpredictable as data volumes scale
  • • Steep learning curve — DQL, Grail, AutomationEngine, and the new app-based platform require significant onboarding investment compared to simpler dashboarding tools
  • • Dashboarding and visualization customization is less flexible than open-source-friendly alternatives like Grafana, with users sometimes constrained to Dynatrace's UI conventions
  • • Smaller teams and startups often find the platform overkill for their needs and difficult to justify versus lighter-weight SaaS APM tools
  • • Migration from the classic Dynatrace experience to the new Grail-based platform has introduced friction for long-time customers retraining on new query languages and apps

What Users Say About Dynatrace

👍 What Users Love

  • ✓Davis AI provides deterministic, causal root-cause analysis rather than just statistical correlation, reducing alert noise and accelerating MTTR in complex distributed systems
  • ✓Single OneAgent deployment automatically discovers and instruments hosts, containers, services, and dependencies — eliminating most manual instrumentation work that competing tools require
  • ✓Grail data lakehouse stores logs, metrics, traces, and events without indexing, enabling fast DQL queries across petabyte-scale data without pre-aggregation trade-offs
  • ✓Unified platform consolidates APM, infrastructure, logs, RUM, synthetic, and runtime security — reducing the need to license and integrate multiple separate tools
  • ✓Strong support for hybrid and multi-cloud environments including AWS, Azure, GCP, Kubernetes, OpenShift, SAP, and mainframe — making it well-suited to large enterprises with heterogeneous stacks
  • ✓Publicly traded company (NYSE:DT) with 20+ years of operating history and enterprise-grade SLAs, security certifications, and 24/7 support phone lines (+1-844-900-3962 for technical support)

👎 Common Concerns

  • ⚠Pricing is widely regarded as among the highest in the observability category, with consumption-based costs that can become unpredictable as data volumes scale
  • ⚠Steep learning curve — DQL, Grail, AutomationEngine, and the new app-based platform require significant onboarding investment compared to simpler dashboarding tools
  • ⚠Dashboarding and visualization customization is less flexible than open-source-friendly alternatives like Grafana, with users sometimes constrained to Dynatrace's UI conventions
  • ⚠Smaller teams and startups often find the platform overkill for their needs and difficult to justify versus lighter-weight SaaS APM tools
  • ⚠Migration from the classic Dynatrace experience to the new Grail-based platform has introduced friction for long-time customers retraining on new query languages and apps

Pricing FAQ

How does Dynatrace's pricing work and is it really enterprise-only?

Dynatrace uses consumption-based pricing across multiple SKUs, including Full-Stack Monitoring (starting around $0.04/hour per 8 GiB host), Infrastructure Monitoring (around $0.01/hour per host), Log Management & Analytics (priced per GiB ingested and queried), Application Security, and Digital Experience Monitoring. While there is a 15-day free trial and self-service signup, the platform's commercial model and feature depth are clearly aimed at mid-market and enterprise buyers. Smaller teams typically find the total cost of ownership higher than lighter SaaS APM alternatives, especially once log ingestion and retention are factored in.

What makes Davis AI different from AI features in other observability tools?

Davis AI is Dynatrace's deterministic causal AI engine that uses the real-time Smartscape topology to trace cause-and-effect relationships rather than relying purely on statistical correlation. This means when an incident occurs, Davis identifies the actual root-cause component (a failing pod, a slow database, a third-party API) along with all impacted entities, instead of surfacing dozens of correlated alerts. Dynatrace has expanded Davis with predictive AI for capacity forecasting and a generative AI copilot (Davis CoPilot) that lets engineers ask natural-language questions and auto-generate DQL queries, dashboards, and workflows.

How does Dynatrace compare to Datadog and New Relic?

Compared to the other major observability tools in our directory, Dynatrace is generally seen as the most automated and AI-driven of the three, with the strongest auto-discovery via OneAgent and the most mature causal root-cause analysis. Datadog typically wins on breadth of integrations (700+) and dashboard flexibility, while New Relic is often more cost-predictable thanks to its per-user pricing model. Dynatrace tends to be the preferred choice for large enterprises with complex Kubernetes, mainframe, or SAP environments where automation reduces operational toil, while Datadog and New Relic are often picked by faster-moving teams that prioritize developer ergonomics or budget predictability.

What environments and technologies does Dynatrace support?

Dynatrace supports a very wide range of environments including AWS, Azure, Google Cloud, IBM Cloud, OpenShift, Kubernetes, VMware, on-premises servers, mainframes (z/OS), and SAP systems. The OneAgent supports major languages including Java, .NET, Node.js, Python, Go, PHP, and Ruby, and integrates with OpenTelemetry for vendor-neutral instrumentation. It also offers prebuilt content for hundreds of technologies through Dynatrace Hub, including databases, message queues, CI/CD platforms, and ITSM tools like ServiceNow, Jira, and PagerDuty.

Is Dynatrace a good fit for application security and DevSecOps?

Yes — Dynatrace Application Security adds runtime vulnerability analytics, runtime application protection, and attack detection on top of the same OneAgent used for observability. Because it observes applications at runtime, it can prioritize CVEs based on whether the vulnerable library is actually loaded and exposed to the public internet, dramatically reducing false positives compared to static SAST tools. Combined with AutomationEngine workflows, security teams can automate remediation tasks like ticket creation, deployment blocks, or runtime mitigations, making Dynatrace a credible DevSecOps platform alongside its observability function.

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More about Dynatrace

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Datadog Pricing

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