Decision comparison
Dynatrace vs Grafana Cloud
Dynatrace and Grafana Cloud reach observability from opposite directions. Dynatrace deploys OneAgent, discovers the estate itself and proposes root causes through Davis AI. Grafana Cloud runs the open LGTM stack as a service — Loki, Grafana, Tempo, Mimir — with open formats throughout and the option to self-host the same stack if you leave.
Direct comparison. These are reviewed substitutes bought for the same job, so the differences below are the ones that decide between them.
All 2 are observability platforms.
Quick Comparison
| Decision factor | Dynatrace | Grafana Cloud |
|---|---|---|
| What it is | An enterprise observability platform with OneAgent auto-instrumentation and the Davis AI engine for root-cause analysis | The managed LGTM stack — Loki for logs, Grafana for dashboards, Tempo for traces, Mimir for metrics — run as a service |
| Emphasis | Automated analysis over an estate the platform discovers for itself | The open LGTM stack run as a service, with the data model and dashboards you already know |
| Instrumentation | OneAgent per host, plus OpenTelemetry | OpenTelemetry and Prometheus exposition, both open standards |
| Analysis | Davis AI proposes a root cause from the discovered topology | Dashboards, correlation and alerting you compose yourself |
| Portability | Telemetry lives in the platform, in its own model | Open formats throughout, with the same stack self-hostable if you leave |
| Cost shape | Annual platform commitment; capability-specific host-hour, memory-GiB-hour and telemetry charges | Free with usage limits; Pro from $19/month plus usage; Enterprise from $25,000 annual spend commitment |
| Best fit | Large estates where nobody can hold the topology in their head | Teams already fluent in Prometheus and Grafana who want it managed |
| Instrumentation path | OpenTelemetry SDKs in Python, Java, Node.js or Go emitting OTLP, or the platform's own agent | OpenTelemetry SDKs in Python, Java, Node.js or Go emitting OTLP, or the platform's own agent |
Dynatrace
- What it is:
- An enterprise observability platform with OneAgent auto-instrumentation and the Davis AI engine for root-cause analysis
- Emphasis:
- Automated analysis over an estate the platform discovers for itself
- Instrumentation:
- OneAgent per host, plus OpenTelemetry
- Analysis:
- Davis AI proposes a root cause from the discovered topology
- Portability:
- Telemetry lives in the platform, in its own model
- Cost shape:
- Annual platform commitment; capability-specific host-hour, memory-GiB-hour and telemetry charges
- Best fit:
- Large estates where nobody can hold the topology in their head
- Instrumentation path:
- OpenTelemetry SDKs in Python, Java, Node.js or Go emitting OTLP, or the platform's own agent
Grafana Cloud
- What it is:
- The managed LGTM stack — Loki for logs, Grafana for dashboards, Tempo for traces, Mimir for metrics — run as a service
- Emphasis:
- The open LGTM stack run as a service, with the data model and dashboards you already know
- Instrumentation:
- OpenTelemetry and Prometheus exposition, both open standards
- Analysis:
- Dashboards, correlation and alerting you compose yourself
- Portability:
- Open formats throughout, with the same stack self-hostable if you leave
- Cost shape:
- Free with usage limits; Pro from $19/month plus usage; Enterprise from $25,000 annual spend commitment
- Best fit:
- Teams already fluent in Prometheus and Grafana who want it managed
- Instrumentation path:
- OpenTelemetry SDKs in Python, Java, Node.js or Go emitting OTLP, or the platform's own agent
Need the cost answer?
Compare Dynatrace, Datadog and New Relic using your workload.
Public signals
Verified factual signals only. Bars appear only for like-for-like metrics with five weekly assessments for every tool; missing evidence stays explicit. These signals do not establish enterprise adoption, product quality, or total cost.
| Metric | Dynatrace | Grafana Cloud |
|---|---|---|
| GitHub commits, 90d(Developer adoption) | 319 | 288 |
| GitHub stars(Developer adoption) | 227 | 798 |
| Search interest(Market interest) | 5 | 1 |
| Hacker News mentions, 90d(Community interest) | 3 | 0 |
| PyPI weekly downloads(Developer adoption) | 27.7k | Not available |
| Stack Overflow questions(Community interest) | 199 | Not available |
| Product Hunt comments(Community interest) | Not available | 3 |
| Product Hunt rating(Community interest) | Not available | 5.0/5 |
| Product Hunt reviews(Community interest) | Not available | 22 |
| Product Hunt votes(Community interest) | Not available | 66 |
As of October 26, 2026 — updated weekly.
Health & risk evidence
Observed public-source checks for mapped package versions and repositories.
Dynatrace
October 26, 2026Package vulnerabilities
PyPI · oneagent-sdk@1.5.2.20260107.153442
0 vulnerabilities
across 1 package
Repository security score
Not available
Grafana Cloud
Package vulnerabilities
Not available
Repository security score
Not available
Interface Preview
Dynatrace
Grafana Cloud
Feature Comparison
| Feature | Dynatrace | Grafana Cloud |
|---|---|---|
| Analysis | ||
| Automatic topology discovery | Full support | Partial support |
| Proposed root cause | Full support | Not verified |
| Real user monitoring | Full support | Partial support |
| Code-level diagnostics | Full support | Partial support |
| Openness | ||
| Open source core | Not verified | Full support |
| Prometheus exposition support | Partial support | Full support |
| Self-host the same stack | Not verified | Full support |
| Open storage formats | Not verified | Full support |
| Platform | ||
| Security monitoring | Full support | Partial support |
| Usable free tier | Not verified | Full support |
| Enterprise access control | Full support | Full support |
| Large-estate coverage | Full support | Full support |
| Standards | ||
| OpenTelemetry ingestion | Full support | Full support |
| Distributed tracing | Full support | Full support |
| Log search | Full support | Full support |
| Metrics dashboards and alerting | Full support | Full support |
Analysis
Automatic topology discovery
Proposed root cause
Real user monitoring
Code-level diagnostics
Openness
Open source core
Prometheus exposition support
Self-host the same stack
Open storage formats
Platform
Security monitoring
Usable free tier
Enterprise access control
Large-estate coverage
Standards
OpenTelemetry ingestion
Distributed tracing
Log search
Metrics dashboards and alerting
Which to choose
Dynatrace and Grafana Cloud reach observability from opposite directions. Dynatrace deploys OneAgent, discovers the estate itself and proposes root causes through Davis AI. Grafana Cloud runs the open LGTM stack as a service — Loki, Grafana, Tempo, Mimir — with open formats throughout and the option to self-host the same stack if you leave.
Best-fit scenarios
Choose Dynatrace if:
Choose Dynatrace when the estate is large enough that keeping a map current is itself the problem. OneAgent discovers processes and dependencies without anyone drawing a map, Davis AI proposes a cause rather than a dashboard, and real user monitoring and security arrive in the same platform.
Choose Grafana Cloud if:
Choose Grafana Cloud when your team already thinks in Prometheus and Grafana and wants it operated for them. Open standards throughout mean the data is portable and the same stack can be self-hosted if the commercial arrangement changes, and the free tier is large enough to be a real starting point.
These scenarios reflect the available product evidence. Your requirements, existing stack, and team expertise should guide the final decision.
Frequently Asked Questions
Does open source matter if we are buying the managed version?
It matters as an exit. Running the open stack as a service means the data model, the query languages and the dashboards are the same ones you could run yourself, so leaving is a migration of operations rather than a rewrite of instrumentation and alerting. That option has value even if you never take it, because it changes the renewal conversation.
What does automatic discovery actually save?
The map. In a large estate the hardest part is knowing what exists and what depends on what, and that knowledge decays as teams ship. An agent that discovers processes and dependencies keeps it current without maintenance, which is the difference between coverage that is real and coverage that was accurate at rollout.
What do these need to run?
An agent or an OpenTelemetry SDK in the application, and a destination. Services in Python, Java, Node.js or Go emit OTLP over HTTP or gRPC, and containers on Kubernetes are instrumented once per pod or once per node depending on the collector you choose. Nothing unusual is required on the application side; the operational weight sits in deciding what to sample, what to retain and for how long.
How portable is the instrumentation?
Both ingest OpenTelemetry, so OTLP instrumentation transfers. Grafana Cloud is the more portable end to end, because its components are the open-source projects themselves and the same stack can run in your own cluster. Dynatrace also runs OneAgent, and OneAgent is what produces the automatic discovery and continuous topology Davis reasons over — capability that standard instrumentation does not provide and does not carry with it. Instrument with OpenTelemetry, and treat agent-derived topology as a deliberate dependency rather than an accident.
What actually drives the cost on each?
Dynatrace draws capability-specific charges from an annual platform commitment. Host-hour and memory-GiB-hour monitoring, log ingestion, retention and queries are distinct meters; log pricing also depends on the selected model. Grafana Cloud has product-specific meters, including billable metric series, logs, traces and profiles. Free has usage limits and 14-day telemetry retention. Pro starts at $19/month plus usage, with 13 months for metrics and 30 days for logs, traces and profiles. Enterprise starts at a $25,000 annual spend commitment; custom retention requires a quote. Include other enabled services and measure operating work on both platforms. Neither the rate cards nor team size establishes a total-cost winner.
Who is each one for?
Dynatrace suits a large estate with a small operations team, where nobody holds the architecture in their head and the leverage comes from a platform that discovers dependencies and proposes causes. Grafana Cloud suits a platform team that already runs Prometheus and Grafana, wants per-signal retention control, and values the option to self-host. Assign an owner for telemetry tuning on either platform. Evaluate how much setup, maintenance and incident investigation each requires before deciding whether automation justifies its cost.
How should we evaluate them?
Send a slice of real traffic to both and then debug a real incident on each. Dashboards demo well and tell you very little; what matters is whether an engineer at 3am can go from an alert to the cause without knowing in advance which dashboard to open. Check instrumentation compatibility, agent dependencies, ingestion charges and trial limits before sending traffic to both platforms; OpenTelemetry support alone does not establish trial cost.