Grafana is an open-source visualization and dashboarding platform ideal for teams managing their own monitoring stacks with lower costs, while Dynatrace is an enterprise AI-powered observability platform offering automatic full-stack monitoring with higher pricing but less operational overhead.
Grafana vs Dynatrace — Side-by-side comparison on A Versus B
Choose Grafana if you have skilled DevOps/SRE teams, require deep customization, manage multiple monitoring tools, and operate under tight budget constraints. Choose Dynatrace if your organization prioritizes rapid time-to-value, wants automatic instrumentation across languages/frameworks, needs AI-driven insights out-of-the-box, and can justify higher enterprise spending for reduced operational complexity.
Open-source observability platform for metrics visualization and dashboarding
Enterprise APM platform with AI-powered root cause analysis and full-stack infrastructure monitoring.
Total Cost of Ownership (Annual for 10,000 hosts)
Structured comparison data for Grafana vs Dynatrace with 208 attributes.
Mean Time to Response (MTTR) Improvement
Supported Technologies (Languages/Frameworks)
Enterprise Annual License Cost (Single Server)
Monthly Platform Cost (100GB/month ingestion)
Mean Time to Resolution (MTTR) Improvement
Setup Time for Multi-Service Environment
Typical Enterprise Annual Cost (1000 hosts)
Total Cost of Ownership (3-year, 500GB/month ingestion)
Required Infrastructure Team Size (100 users)
Grafana vs Dynatrace — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for Grafana vs Dynatrace.
Can Grafana replace Dynatrace completely?
Partially. Grafana can visualize the same metrics Dynatrace collects if you add separate agents (Prometheus Node Exporter, Telegraf, Elastic Agent), but you'll need to manually configure monitoring, build your own anomaly detection logic, and won't have Dynatrace's automatic instrumentation or AI-powered root cause analysis. Total cost becomes comparable once you factor in engineering effort.
What's the real cost difference over 3 years?
For a mid-size deployment (1,000 hosts): Grafana self-hosted costs $15K-$45K annually ($45K-$135K over 3 years) plus 3-4 FTE staff ($300K-$400K salary costs). Dynatrace averages $200K-$500K annually ($600K-$1.5M over 3 years) but requires minimal staff. Grafana is cheaper if you have in-house expertise; Dynatrace wins on total operational cost if staff time is factored in.
How long until Grafana gets AI anomaly detection like Dynatrace?
Grafana has added some ML features (Grafana ML for forecasting, released 2023), but native AI-powered root cause analysis comparable to Dynatrace's Davis AI is not yet available. You can integrate third-party ML services or use community plugins, but it requires additional work and isn't as polished as Dynatrace's built-in solution.
Which is better for Kubernetes monitoring?
Dynatrace has native Kubernetes support with automatic service discovery and dashboard generation. Grafana requires installing Prometheus with kube-state-metrics and node-exporter, then manually building dashboards. Dynatrace gets visibility faster (days vs. weeks), but Grafana offers more customization once deployed.
Can I use Grafana and Dynatrace together?
Yes. Many enterprises use Dynatrace for production monitoring/AI analysis and Grafana for cost-focused metrics visualization, internal tools, or non-critical systems. Dynatrace can push data to Grafana via APIs, and Grafana can query Dynatrace metrics, though this creates operational complexity.