software
Grafana vs Dynatrace 2026 - Comparison
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
Open-source observability platform for metrics visualization and dashboarding
Engineering teams with strong DevOps expertise, cost-conscious organizations, multi-vendor environments requiring unified dashboards, and companies needing full control over monitoring stack
Score63%
VS
Dynatrace
Enterprise APM platform with AI-powered root cause analysis and full-stack infrastructure monitoring.
Large enterprises with complex distributed systems, organizations prioritizing rapid deployment, teams lacking monitoring infrastructure expertise, and companies willing to invest in premium support and automated intelligence
Score63%
208 attributes7 differences16 pros/cons
Quick Answer
AI SummaryGrafana 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.
Our Verdict
AI-assistedChoose 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.
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Grafana
8.8/10
Dynatrace
6.2/10
Choose Grafana if
Best pickEngineering teams with strong DevOps expertise, cost-conscious organizations, multi-vendor environments requiring unified dashboards, and companies needing full control over monitoring stack
Choose Dynatrace if
Large enterprises with complex distributed systems, organizations prioritizing rapid deployment, teams lacking monitoring infrastructure expertise, and companies willing to invest in premium support and automated intelligence
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Key Differences at a Glance
- Architecture:✓ Dynatrace wins(All-in-one SaaS with built-in agents and AI-powered analytics vs Open-source visualization layer; requires separate data collection tools)
- Total Cost of Ownership (Annual for 10,000 hosts):✓ Grafana wins($50,000-$150,000 (self-managed) vs $500,000-$2,000,000 (managed service))
- Setup Time:✓ Dynatrace wins(3-5 days with auto-instrumentation vs 2-4 weeks with manual configuration)
Key Facts & Figures
144 numeric metrics compared
| Metric | Grafana | Dynatrace | Ratio |
|---|---|---|---|
| Supported Data Sources(count) | 70+ | — | — |
| Starting Monthly Cost(USD) | Free (open-source) | — | — |
| Time to First Dashboard(minutes) | 60-120 | — | — |
| Pre-built Integrations(count) | 300+ | — | — |
| Community Size(millions of users) | 500K+ users | — | — |
| Base Monthly Cost Per User(USD) | $69 | — | — |
| Customer Retention Rate(%) | 94% | — | — |
| GitHub Stars (Community Adoption)(count) | 58,000+ (as of 2026) | — | — |
| Data Sources Supported(integrations) | 90+ (Prometheus, Elasticsearch, Datadog, etc.) | — | — |
| Memory Usage (Typical Instance)(MB) | 200-500 | — | — |
| Query Language Learning Curve(complexity rating) | 2-4 (depends on datasource type) | — | — |
| Time to First Dashboard(days) | 30-60 (needs datasource setup) | — | — |
| Base Pricing (Annual, 100 hosts)(USD) | $0 (self-hosted) | $50,000 | |
| Initial Deployment Time(weeks) | 14-28 days | 3-5 days | |
| Data Source Integrations(count) | 800+ | 600+ | |
| Supported Technologies (Languages/Frameworks)(count) | 300+ via integrations | 100+ with native agents | |
| AI-Powered Anomaly Detection Accuracy(percent) | Not available | 85% | — |
| Alert Management Channels(count) | 50+ | 40+ | |
| Grafana/Dynatrace Community Size(thousands of members) | 500K+ monthly active users | 100K+ enterprise customers | |
| Required IT Staff for 10,000 hosts(FTE) | 3-5 FTE | 0.5-1 FTE | |
| Memory Footprint (Minimal Setup)(MB) | ~200 MB | — | — |
| Setup Time (Basic Production)(minutes) | 15-30 minutes | — | — |
| Minimum Monthly Cost (Small Org)(USD) | $0 (open-source) or $9 (Grafana Cloud) | — | — |
| Data Source Integrations Available(count) | 450+ pre-built plugins | — | — |
| Supported APM Frameworks(count) | 100+ via plugins (manual integration required) | — | — |
| Setup Time for Basic Monitoring(days) | 2-5 days (infrastructure knowledge required) | — | — |
| Data Retention (Free Tier)(months) | Unlimited (self-hosted) or 15 days (Grafana Cloud free) | — | — |
| User Seats Included (Starter)(seats) | Unlimited on self-hosted; 1 on Grafana Cloud free | — | — |
| Dashboard Creation Time(minutes) | 5-10 minutes | — | — |
| Cloud Hosting Starting Price(USD/month) | $79/month | — | — |
| Self-Hosted Cost(USD/month) | $0 (free open-source) | — | — |
| Starting Monthly Cost Per User(USD) | $0 (open-source) | — | — |
| Native Data Connectors(count) | 60+ | — | — |
| Minimum Dashboard Refresh Interval(seconds) | 0.001 seconds (milliseconds) | — | — |
| Visualization Chart Types(count) | 15+ | — | — |
| Enterprise Annual License Cost (Single Server)(USD) | $0 (self-hosted free tier) | — | — |
| Time to First Dashboard Creation(minutes) | 5-10 (intuitive interface) | — | — |
| Base Monthly Cost (Single User Cloud)(USD) | $10 (Grafana Cloud Starter) | — | — |
| Annual Cost (1GB/day Log Ingestion)(USD) | $2,400-$7,200 | — | — |
| Log Query Response Time(milliseconds) | 5,000-10,000 (Loki) | — | — |
| Event Ingestion Rate (Single Indexer)(events/sec) | 1,000-2,000 | — | — |
| Native Data Source Integrations(count) | 470+ integrations | — | — |
| Built-In Machine Learning Algorithms(count) | 3-5 (basic anomaly detection) | — | — |
| Minimum RAM Requirement (Self-Hosted)(GB) | <2 | — | — |
| GitHub Stars(stars) | 56,000 | — | — |
| Initial Setup Time(minutes) | 15-30 | — | — |
| Enterprise License Cost (Annual)(USD) | $12,000 for Grafana Enterprise | — | — |
| Real-Time Dashboard Latency(milliseconds) | 50-500 | — | — |
| Monthly Cost Per Host(USD) | $0-3 (self-hosted) | — | — |
| Time to Production Deployment(days) | 30-240 minutes (varies) | — | — |
| Annual Cost (100 hosts, moderate usage)(USD) | $0-2,500 (self-hosted) | — | — |
| Base License Cost (Monthly)(USD) | $0 (open-source) | $600-$5000+ (SaaS only) | |
| Supported Data Sources(count) | 60+ official plugins + 150+ community plugins | 40+ native integrations | |
| Automatic Instrumentation Coverage(technologies) | Not applicable (requires manual integration) | 650+ supported technologies | — |
| Time to First Production Metrics(weeks) | 2-4 weeks (with data pipeline setup) | 1-2 weeks (with auto-instrumentation) | |
| Community Dashboard Templates(dashboards) | 10,000+ community-created dashboards | Curated pre-built dashboards (proprietary) | |
| Minimum Deployment Memory Requirement(MB) | 500 MB | 2000+ MB (full SaaS service) | |
| Starting Price (Monthly)(USD) | Free (open-source) | — | — |
| Data Source Connectors(count) | 400+ plugins (Prometheus, InfluxDB, CloudWatch, etc.) | — | — |
| Minimum Dashboard Refresh Rate(seconds) | 5-10 seconds (typical) | — | — |
| User Onboarding Time(hours) | 7-14 days (JSON, API, plugin config) | — | — |
| Annual per-User Cost (Creator Tier)(USD) | $120-$3,588/year (Grafana Cloud) | — | — |
| Base License Cost (Annual)(USD) | $0 (open-source) | — | — |
| Typical Enterprise Implementation Cost(USD) | $10,000-$30,000 | — | — |
| Average Search Query Time (1GB dataset)(seconds) | 0.5-2 seconds | — | — |
| Built-in Machine Learning Models(count) | 3-5 (via plugins) | — | — |
| Typical Deployment Time(hours) | 2-4 weeks | — | — |
| Data Source Support(integrations) | 80+ | — | — |
| Time to Deploy Dashboard(minutes) | 5-10 minutes with templates | — | — |
| Notification Channels(integrations) | 50+ | — | — |
| Base Monthly Cost(USD) | $0 (open-source) or $231 (Pro) | $400 | |
| Free Tier Data Retention(days) | 15 days | — | — |
| APM Language Support(languages) | 5+ (requires manual agent setup) | — | — |
| Deployment Models Supported(count) | 4 options (Self-hosted, Cloud, Hybrid, Kubernetes) | — | — |
| GitHub Stars (Community Traction)(thousands) | 18.5k stars | — | — |
| Supported Technology Integrations(count) | 600+ | 600+ | |
| Metric Data Retention(days) | 15 days | 15 days | |
| Trace Data Retention(days) | 8 days | 8 days | |
| Typical Implementation Timeline(days) | 6-12 weeks | 6-12 weeks | |
| Cost Per GB Ingested(USD per GB/month) | $15-25+ | $15-25+ | |
| Typical Enterprise Customer Annual Cost(USD) | $150,000-500,000 | $150,000-500,000 | |
| Free Trial Duration(days) | 14 days (limited) | 14 days (limited) | |
| Supported Programming Languages(count) | 50+ languages | 50+ languages | |
| Metrics Data Retention(days) | 15 days | 15 days | |
| API Request Rate Limit(requests per minute) | 1,000 req/min | 1,000 req/min | |
| Base Monthly Cost (100 GB/month)(USD) | $5,000-8,000 | $5,000-8,000 | |
| Implementation Timeline(weeks) | 2-4 weeks | 2-4 weeks | |
| Out-of-Box Integrations(count) | 500+ | 500+ | |
| Max Data Retention (free tier)(days) | 15 days | 15 days | |
| Typical Implementation Time(weeks) | 3 weeks | 3 weeks | |
| Base Monthly Cost per Host(USD) | $50/month | $50/month | |
| Third-Party Integrations(integrations) | 450+ integrations | 450+ integrations | |
| Included Infrastructure Metrics(metrics per host) | 70 metrics | 70 metrics | |
| Custom Metrics Cost(USD per metric/month) | $0.10 per metric | $0.10 per metric | |
| Average MTTR Improvement(percent reduction) | 60% reduction | 60% reduction | |
| Monthly Platform Cost (100GB/month ingestion)(USD) | $2,500-$5,000 | $2,500-$5,000 | |
| Supported Programming Languages (APM)(languages) | 95+ languages | 95+ languages | |
| Mean Time to Resolution (MTTR) Improvement(percentage reduction) | 40-60% reduction with AI | 40-60% reduction with AI | |
| Setup Time for Multi-Service Environment(days) | 2-4 days (automatic) | 2-4 days (automatic) | |
| Data Retention (Standard Plan)(days) | 35 days | 35 days | |
| Free Trial Period(days) | 15 days | 15 days | |
| User Satisfaction Score (G2 Reviews)(out of 5.0) | 4.5 stars (1,200+ reviews) | 4.5 stars (1,200+ reviews) | |
| Monthly Cost Per Host (Enterprise)(USD) | $25-40 | $25-40 | |
| Native Integrations Available(count) | 350+ | 350+ | |
| Average Deployment Time(seconds) | 3 hours | 3 hours | |
| G2 Customer Satisfaction Rating (2024)(stars) | 4.6/5.0 | 4.6/5.0 | |
| G2 Review Count (2024)(reviews) | 1,200+ | 1,200+ | |
| Total Cost of Ownership (Year 1)(USD) | $8,000-$24,000+ | $8,000-$24,000+ | |
| Average Time to Root Cause (MTTR)(minutes) | 15-30 (with Davis AI) | 15-30 (with Davis AI) | |
| Supported Technologies(integrations) | 650+ out-of-box | 650+ out-of-box | |
| Data Retention (Default)(months) | 15-30 days (configurable) | 15-30 days (configurable) | |
| Ingest Rate (Typical)(events per second) | 100,000+ EPS per cluster | 100,000+ EPS per cluster | |
| Log Retention (Standard)(days) | 5 days | 5 days | |
| Starting Price Per Host(USD/month) | $45-65 per host | $45-65 per host | |
| Native Integrations(count) | 700+ pre-built integrations | 700+ pre-built integrations | |
| Agent Installation Complexity(agents required) | 1 unified agent (OneAgent) | 1 unified agent (OneAgent) | |
| Gartner Peer Reviews Score(out of 5.0) | 4.7/5.0 (1,800+ reviews) | 4.7/5.0 (1,800+ reviews) | |
| Typical Enterprise Annual Cost (1000 hosts)(USD) | $540K-780K | $540K-780K | |
| Mean Time to Resolution (MTTR)(minutes reduction) | 45% faster than legacy APM | 45% faster than legacy APM | |
| Time to First Production Insight(days) | 3-7 days | 3-7 days | |
| Starting Annual Cost(USD) | $15,000 | $15,000 | |
| Community Size & Resources(active contributors) | ~10,000 community members | ~10,000 community members | |
| Starting Monthly Cost(USD) | $500-800 | $500-800 | |
| Log Ingestion Cost per GB(USD) | $1.20-1.60 | $1.20-1.60 | |
| Average Time to Value(days) | < 1 day | < 1 day | |
| Total Cost of Ownership (3-year, 500GB/month ingestion)(USD) | $360,000 (6,000 GB × $3/GB × 3 years + support) | $360,000 (6,000 GB × $3/GB × 3 years + support) | |
| Number of Pre-built Integrations(count) | 600+ | 600+ | |
| Data Retention Default(months) | 15 months | 15 months | |
| Query Performance on 1TB Index(milliseconds) | < 500ms (P95) | < 500ms (P95) | |
| Required Infrastructure Team Size (100 users)(FTEs) | 0.25 (mostly monitoring) | 0.25 (mostly monitoring) | |
| Starting Annual Price(USD) | $52,500 | $52,500 | |
| Average Time to Root Cause(minutes) | 2.5 minutes | 2.5 minutes | |
| Customer Satisfaction (NPS)(score) | 68 NPS | 68 NPS | |
| Data Retention Standard(days) | 365 days | 365 days | |
| API Endpoints for Integration(count) | 400+ integrations | 400+ integrations | |
| Typical Monthly Cost (100 hosts)(USD) | $5,000-15,000 (host-based licensing) | $5,000-15,000 (host-based licensing) | |
| Average Implementation Duration(months) | 4-8 weeks | 4-8 weeks | |
| AI-Driven Root Cause Automation(% of issues auto-detected) | ~75-85% with Davis AI | ~75-85% with Davis AI | |
| Standard Data Retention(months) | 15 months | 15 months | |
| Typical Enterprise Customer Size(employees) | 5,000+ (enterprise focus) | 5,000+ (enterprise focus) | |
| Number of Out-of-Box Integrations(integrations) | 500+ (incl. Slack, Splunk, Okta) | 500+ (incl. Slack, Splunk, Okta) | |
| Monthly Pricing (Small Organization)(USD) | $12,000-20,000 | $12,000-20,000 | |
| Ideal Organization Size(engineers) | 500+ engineers | 500+ engineers | |
| Time to First Alert(minutes) | 2-5 minutes (after setup) | 2-5 minutes (after setup) |
Sourced from publicly available data ·
Key Differences
7 attributes compared head-to-head
Dynatrace leads
Grafana
Attribute
Dynatrace
- Open-source visualization layer; requires separate data collection toolsArchitectureAll-in-one SaaS with built-in agents and AI-powered analytics(winner)
- $50,000-$150,000 (self-managed)(winner)Total Cost of Ownership (Annual for 10,000 hosts)$500,000-$2,000,000 (managed service)
- 2-4 weeks with manual configurationSetup Time3-5 days with auto-instrumentation(winner)
- Limited; requires third-party integrationsAI/ML CapabilitiesNative AI-powered anomaly detection and root cause analysis(winner)
- 800+ integrations and plugins(winner)Data Source Support600+ integrations with automatic discovery
- High; requires dedicated team for maintenanceOperational OverheadLow; fully managed by vendor(winner)
- Unlimited; source code available(winner)Customization FlexibilityLimited to vendor configuration options
- Architecture
Grafana
Open-source visualization layer; requires separate data collection tools
Dynatrace
All-in-one SaaS with built-in agents and AI-powered analytics(winner)
- Total Cost of Ownership (Annual for 10,000 hosts)
Grafana
$50,000-$150,000 (self-managed)(winner)
Dynatrace
$500,000-$2,000,000 (managed service)
- Setup Time
Grafana
2-4 weeks with manual configuration
Dynatrace
3-5 days with auto-instrumentation(winner)
- AI/ML Capabilities
Grafana
Limited; requires third-party integrations
Dynatrace
Native AI-powered anomaly detection and root cause analysis(winner)
- Data Source Support
Grafana
800+ integrations and plugins(winner)
Dynatrace
600+ integrations with automatic discovery
- Operational Overhead
Grafana
High; requires dedicated team for maintenance
Dynatrace
Low; fully managed by vendor(winner)
- Customization Flexibility
Grafana
Unlimited; source code available(winner)
Dynatrace
Limited to vendor configuration options
Full Comparison
| Attribute | Grafana | Dynatrace |
|---|---|---|
| Supported Data Sources(count) | 70+ | — |
| Pre-built Integrations(count) | 300+ | — |
| Data Source Integrations(count) | 800+(winner) | 600+ |
| Native Data Connectors(count) | 60+ | — |
| Supported Data Sources(count) | 60+ official plugins + 150+ community plugins(winner) | 40+ native integrations |
Show 2 more attributesData Source Connectors(count) 400+ plugins (Prometheus, InfluxDB, CloudWatch, etc.) — API Endpoints for Integration(count) 400+ integrations — | ||
| Self-Hosting Support | Yes, full support | — |
| Open-Source Self-Hosted Availability(null) | Available (Apache 2.0) | — |
| Setup Time (Basic Production)(minutes) | 15-30 minutes | — |
| Docker Deployment | Single container with optional Prometheus | — |
| Time to First Production Metrics(weeks) | 2-4 weeks (with data pipeline setup) | 1-2 weeks (with auto-instrumentation)(winner) |
Show 4 more attributesDeployment Models Supported(count) 4 options (Self-hosted, Cloud, Hybrid, Kubernetes) — Implementation Time(weeks) 40-80+ hours — Agent Installation Complexity(agents required) 1 unified agent (OneAgent) — Average Implementation Duration(months) 4-8 weeks — | ||
| Starting Monthly Cost(USD) | Free (open-source) | — |
| Base Monthly Cost Per User(USD) | $69 | — |
| Free Tier User Limit(users) | Unlimited users | — |
| Cloud Hosting Starting Price(USD/month) | $79/month | — |
| Self-Hosted Cost(USD/month) | $0 (free open-source) | — |
Show 24 more attributesStarting Monthly Cost Per User(USD) $0 (open-source) — Enterprise Annual License Cost (Single Server)(USD) $0 (self-hosted free tier) — Base Monthly Cost (Single User Cloud)(USD) $10 (Grafana Cloud Starter) — Annual Cost (1GB/day Log Ingestion)(USD) $2,400-$7,200 — Enterprise License Cost (Annual)(USD) $12,000 for Grafana Enterprise — Monthly Cost Per Host(USD) $0-3 (self-hosted) — Annual Cost (100 hosts, moderate usage)(USD) $0-2,500 (self-hosted) — Base License Cost (Monthly)(USD) $0 (open-source) $600-$5000+ (SaaS only) Starting Price (Monthly)(USD) Free (open-source) — Annual per-User Cost (Creator Tier)(USD) $120-$3,588/year (Grafana Cloud) — Base License Cost (Annual)(USD) $0 (open-source) — Typical Enterprise Implementation Cost(USD) $10,000-$30,000 — Base Monthly Cost(USD) $0 (open-source) or $231 (Pro) $400 Cost Per GB Ingested(USD per GB/month) $15-25+ — Typical Enterprise Customer Annual Cost(USD) $150,000-500,000 — Base Monthly Cost (100 GB/month)(USD) $5,000-8,000 — Base Monthly Cost per Host(USD) $50/month — Custom Metrics Cost(USD per metric/month) $0.10 per metric — Monthly Cost Per Host (Enterprise)(USD) $25-40 — Starting Price Per Host(USD/month) $45-65 per host — Starting Annual Cost(USD) $15,000 — Starting Monthly Cost(USD) $500-800 — Log Ingestion Cost per GB(USD) $1.20-1.60 — Typical Monthly Cost (100 hosts)(USD) $5,000-15,000 (host-based licensing) — | ||
| Time to First Dashboard(minutes) | 60-120 | — |
| Time to First Dashboard(days) | 30-60 (needs datasource setup) | — |
| Initial Deployment Time(weeks) | 14-28 days | 3-5 days(winner) |
| Typical Deployment Time(hours) | 2-4 weeks | — |
| Average Time to Value(days) | < 1 day | — |
| Log Management | Requires Loki plugin | — |
| APM Capabilities | Plugin-based with limited support | — |
| On-Call Scheduling Features(null) | Requires integration (OnCall) | — |
| Data Sources Supported(integrations) | 90+ (Prometheus, Elasticsearch, Datadog, etc.) | — |
| Built-in Alerting Capabilities(null) | Basic (via connected datasources) | — |
Show 22 more attributesAI-Powered Anomaly Detection Accuracy(percent) Not available 85% Alert Management Channels(count) 50+ 40+ Log Search Capability Basic text filtering — APM Features Limited (requires integration with APM platforms) — Visualization Chart Types(count) 15+ — Native Data Source Integrations(count) 470+ integrations — Full-Text Log Indexing No (time-series focused) — Built-in Machine Learning Models(count) 3-5 (via plugins) — Native APM Integration No (plugin-based) — APM Language Support(languages) 5+ (requires manual agent setup) — Dashboard Customization Level Unlimited panels, custom plugins, full code access — AI/ML Anomaly Detection Basic threshold-based alerts only — Out-of-Box Integrations(count) 500+ — Automatic Code Instrumentation Native zero-code instrumentation — Native Kubernetes Support Built-in Kubernetes Observer — Third-Party Integrations(integrations) 450+ integrations — Data Retention (Standard Plan)(days) 35 days — Kubernetes/Container Auto-Discovery(capability) Native, automatic service mapping — Native Integrations Available(count) 350+ — Log Management Included(null) Available but often separate — Data Retention Standard(days) 365 days — Infrastructure Monitoring Breadth(coverage %) Full-stack (apps, infra, K8s, serverless, on-prem) — | ||
| Community Size(millions of users) | 500K+ users | — |
| GitHub Stars (Community Adoption)(count) | 58,000+ (as of 2026) | — |
| Grafana/Dynatrace Community Size(thousands of members) | 500K+ monthly active users(winner) | 100K+ enterprise customers |
| GitHub Stars (Community Traction)(thousands) | 18.5k stars | — |
| Community Size(members) | 5,000+ (proprietary) | — |
| Mean Time to Response (MTTR) Improvement(percent) | Not measured | — |
| Alert Fatigue Reduction(percent) | Alert grouping available | — |
| Default Data Retention(days) | None (external source dependent) | — |
| Memory Usage (Typical Instance)(MB) | 200-500 | — |
| Memory Footprint (Minimal Setup)(MB) | ~200 MB | — |
Show 14 more attributesMinimum Dashboard Refresh Interval(seconds) 0.001 seconds (milliseconds) — Log Query Response Time(milliseconds) 5,000-10,000 (Loki) — Event Ingestion Rate (Single Indexer)(events/sec) 1,000-2,000 — Real-Time Dashboard Latency(milliseconds) 50-500 — Minimum Deployment Memory Requirement(MB) 500 MB 2000+ MB (full SaaS service) Minimum Dashboard Refresh Rate(seconds) 5-10 seconds (typical) — Average Search Query Time (1GB dataset)(seconds) 0.5-2 seconds — Time to Deploy Dashboard(minutes) 5-10 minutes with templates — Free Tier Data Retention(days) 15 days — Average Deployment Time(seconds) 3 hours — Average Time to Root Cause (MTTR)(minutes) 15-30 (with Davis AI) — Mean Time to Resolution (MTTR)(minutes reduction) 45% faster than legacy APM — Query Performance on 1TB Index(milliseconds) < 500ms (P95) — Average Time to Root Cause(minutes) 2.5 minutes — | ||
| Customer Retention Rate(%) | 94% | — |
| Gartner Peer Reviews Score(out of 5.0) | 4.7/5.0 (1,800+ reviews) | — |
| Query Language Learning Curve(complexity rating) | 2-4 (depends on datasource type) | — |
| Dashboard Creation Time(minutes) | 5-10 minutes | — |
| User Onboarding Time(hours) | 7-14 days (JSON, API, plugin config) | — |
| Learning Curve(difficulty rating) | 1-2 months | — |
| Standalone Operation | No—requires external datasource | — |
| Base Pricing (Annual, 100 hosts)(USD) | $0 (self-hosted)(winner) | $50,000 |
| Total Cost of Ownership (Year 1)(USD) | $8,000-$24,000+ | — |
| Total Cost of Ownership (3-year, 500GB/month ingestion)(USD) | $360,000 (6,000 GB × $3/GB × 3 years + support) | — |
| Starting Annual Price(USD) | $52,500 | — |
| Monthly Pricing (Small Organization)(USD) | $12,000-20,000 | — |
| Supported Technologies (Languages/Frameworks)(count) | 300+ via integrations(winner) | 100+ with native agents |
| Data Source Support(integrations) | 80+ | — |
| Supported Programming Languages(count) | 50+ languages | — |
| Supported Technologies(integrations) | 650+ out-of-box | — |
| Required IT Staff for 10,000 hosts(FTE) | 3-5 FTE | 0.5-1 FTE(winner) |
| Infrastructure Setup Complexity(DevOps hours) | 20-40 hours (minimal) | — |
| Required Infrastructure Team Size (100 users)(FTEs) | 0.25 (mostly monitoring) | — |
| Commercial Support Cost(USD/month) | $25-150+ per user | — |
| Open Source License Type | AGPL v3 (user-friendly for most use cases) | — |
| Query Language Complexity | PromQL, SQL, or source-native language | — |
| Built-in Alerting Rules(feature) | Visualization only (external routing required) | — |
| Notification Channels(integrations) | 50+ | — |
| Minimum Monthly Cost (Small Org)(USD) | $0 (open-source) or $9 (Grafana Cloud) | — |
| Monthly Platform Cost (100GB/month ingestion)(USD) | $2,500-$5,000 | — |
| Data Source Integrations Available(count) | 450+ pre-built plugins | — |
| Supported APM Frameworks(count) | 100+ via plugins (manual integration required) | — |
| Setup Time for Basic Monitoring(days) | 2-5 days (infrastructure knowledge required) | — |
| Time to First Dashboard Creation(minutes) | 5-10 (intuitive interface) | — |
| AI Anomaly Detection | Limited; basic alerting rules, ML via separate module | Proactive Davis AI engine |
| AI Root Cause Analysis(null) | Advanced Davis AI with causality mapping | — |
| AI-Powered Root Cause Analysis(native capability) | Davis AI included | — |
| Enterprise Support SLA | Community support; no guaranteed SLA | — |
| Data Retention (Free Tier)(months) | Unlimited (self-hosted) or 15 days (Grafana Cloud free) | — |
| Metric Data Retention(days) | 15 days | — |
| Trace Data Retention(days) | 8 days | — |
| Metrics Data Retention(days) | 15 days | — |
| Max Data Retention (free tier)(days) | 15 days | — |
Show 3 more attributesData Retention (Default)(months) 15-30 days (configurable) — Log Retention (Standard)(days) 5 days — Standard Data Retention(months) 15 months — | ||
| User Seats Included (Starter)(seats) | Unlimited on self-hosted; 1 on Grafana Cloud free | — |
| Maximum Dashboard Rows Per Organization(count) | Unlimited | — |
| Ingest Rate (Typical)(events per second) | 100,000+ EPS per cluster | — |
| Row-Level Security (RLS) | Supported via RBAC and data source filtering | — |
| Enterprise Security Features(count) | Basic RBAC, no SIEM module | — |
| Enterprise Compliance(certifications) | SOC 2, ISO 27001 | — |
| Built-In Machine Learning Algorithms(count) | 3-5 (basic anomaly detection) | — |
| Minimum RAM Requirement (Self-Hosted)(GB) | <2 | — |
| Deployment Flexibility | Self-hosted, Docker, K8s, multi-cloud, air-gapped | SaaS only (limited on-premises for enterprise) |
| Deployment Options | Self-hosted, Docker, Kubernetes, Cloud | — |
| GitHub Stars(stars) | 56,000 | — |
| Initial Setup Time(minutes) | 15-30 | — |
| SQL Query Support | Limited—primarily Prometheus-style queries | — |
| Built-in APM | No, requires external tools | — |
| AI/ML Analytics | No native features | — |
| Time to Production Deployment(days) | 30-240 minutes (varies) | — |
| Self-Hosted Deployment | Fully supported | — |
| Automatic Instrumentation Coverage(technologies) | Not applicable (requires manual integration) | 650+ supported technologies |
| AI-Powered Anomaly Detection(built-in) | Not included (requires manual alerting rules) | Yes (Davis AI engine) |
| Community Dashboard Templates(dashboards) | 10,000+ community-created dashboards(winner) | Curated pre-built dashboards (proprietary) |
| Native Integrations(count) | 700+ pre-built integrations | — |
| Number of Out-of-Box Integrations(integrations) | 500+ (incl. Slack, Splunk, Okta) | — |
| Advanced Statistical Functions(count) | Basic math and aggregation functions | — |
| Full-Text Search Optimization | Basic text filters | — |
| Supported Technology Integrations(count) | 600+ | — |
| Typical Implementation Timeline(days) | 6-12 weeks | — |
| Free Trial Duration(days) | 14 days (limited) | — |
| Setup Time for Multi-Service Environment(days) | 2-4 days (automatic) | — |
| Free Trial Period(days) | 15 days | — |
| Infrastructure Monitoring Depth(scope level) | Full-stack (hosts, containers, DBs, k8s) | — |
| API Request Rate Limit(requests per minute) | 1,000 req/min | — |
| Implementation Timeline(weeks) | 2-4 weeks | — |
| Code-Level Instrumentation Depth(null) | Full bytecode line-level | — |
| Automatic Anomaly Detection(null) | ML-based automatic baselines | — |
| Typical Implementation Time(weeks) | 3 weeks | — |
| Included Infrastructure Metrics(metrics per host) | 70 metrics | — |
| Code-Level Profiling Capability | Continuous profiling with memory/CPU/I/O analysis | — |
| Minimum Contract Term(months) | 12-month commitment | — |
| Root Cause Analysis Technology | AI-driven Davis engine with code-level insights | — |
| Average MTTR Improvement(percent reduction) | 60% reduction | — |
| Mean Time to Resolution (MTTR) Improvement(percentage reduction) | 40-60% reduction with AI | — |
| Supported Programming Languages (APM)(languages) | 95+ languages | — |
| User Satisfaction Score (G2 Reviews)(out of 5.0) | 4.5 stars (1,200+ reviews) | — |
| APM Code-Level Detail(null) | Full transaction tracing | — |
| G2 Customer Satisfaction Rating (2024)(stars) | 4.6/5.0 | — |
| Customer Satisfaction (NPS)(score) | 68 NPS | — |
| G2 Review Count (2024)(reviews) | 1,200+ | — |
| API Complexity(learning effort) | Simplified REST API with UI-first approach | — |
| Setup Time(minutes) | 14-28 days | — |
| AI Root Cause Analysis Capability(dependency hops) | Automatic detection up to 4+ hops | — |
| Typical Enterprise Annual Cost (1000 hosts)(USD) | $540K-780K | — |
| Time to First Production Insight(days) | 3-7 days | — |
| Query Language Flexibility(flexibility score) | Limited to predefined queries and dashboards | — |
| Community Size & Resources(active contributors) | ~10,000 community members | — |
| Number of Pre-built Integrations(count) | 600+ | — |
| Supported Data Types(types) | Logs, metrics, traces, user sessions, synthetics | — |
| Data Retention Default(months) | 15 months | — |
| Kubernetes Cluster Support(native capability) | Full native support with auto-discovery | — |
| Deployment Models(count) | SaaS, on-premise, hybrid | — |
| AI-Driven Root Cause Automation(% of issues auto-detected) | ~75-85% with Davis AI | — |
| Mobile App Monitoring Support | Limited third-party integration only | — |
| Typical Enterprise Customer Size(employees) | 5,000+ (enterprise focus) | — |
| AI Root Cause Analysis Sophistication(capability level) | Advanced (causal, predictive, auto-remediation) | — |
| Ideal Organization Size(engineers) | 500+ engineers | — |
| Time to First Alert(minutes) | 2-5 minutes (after setup) | — |
GrafanaDynatraceSupported Data Sources(count)
70+
—
Pre-built Integrations(count)
300+
—
Data Source Integrations(count)
800+
600+
Native Data Connectors(count)
60+
—
Supported Data Sources(count)
60+ official plugins + 150+ community plugins
40+ native integrations
Show 2 more attributes
Data Source Connectors(count)
400+ plugins (Prometheus, InfluxDB, CloudWatch, etc.)
—
API Endpoints for Integration(count)
400+ integrations
—
Self-Hosting Support
Yes, full support
—
Open-Source Self-Hosted Availability(null)
Available (Apache 2.0)
—
Setup Time (Basic Production)(minutes)
15-30 minutes
—
Docker Deployment
Single container with optional Prometheus
—
Time to First Production Metrics(weeks)
2-4 weeks (with data pipeline setup)
1-2 weeks (with auto-instrumentation)
Show 4 more attributes
Deployment Models Supported(count)
4 options (Self-hosted, Cloud, Hybrid, Kubernetes)
—
Implementation Time(weeks)
40-80+ hours
—
Agent Installation Complexity(agents required)
1 unified agent (OneAgent)
—
Average Implementation Duration(months)
4-8 weeks
—
Starting Monthly Cost(USD)
Free (open-source)
—
Base Monthly Cost Per User(USD)
$69
—
Free Tier User Limit(users)
Unlimited users
—
Cloud Hosting Starting Price(USD/month)
$79/month
—
Self-Hosted Cost(USD/month)
$0 (free open-source)
—
Show 24 more attributes
Starting Monthly Cost Per User(USD)
$0 (open-source)
—
Enterprise Annual License Cost (Single Server)(USD)
$0 (self-hosted free tier)
—
Base Monthly Cost (Single User Cloud)(USD)
$10 (Grafana Cloud Starter)
—
Annual Cost (1GB/day Log Ingestion)(USD)
$2,400-$7,200
—
Enterprise License Cost (Annual)(USD)
$12,000 for Grafana Enterprise
—
Monthly Cost Per Host(USD)
$0-3 (self-hosted)
—
Annual Cost (100 hosts, moderate usage)(USD)
$0-2,500 (self-hosted)
—
Base License Cost (Monthly)(USD)
$0 (open-source)
$600-$5000+ (SaaS only)
Starting Price (Monthly)(USD)
Free (open-source)
—
Annual per-User Cost (Creator Tier)(USD)
$120-$3,588/year (Grafana Cloud)
—
Base License Cost (Annual)(USD)
$0 (open-source)
—
Typical Enterprise Implementation Cost(USD)
$10,000-$30,000
—
Base Monthly Cost(USD)
$0 (open-source) or $231 (Pro)
$400
Cost Per GB Ingested(USD per GB/month)
$15-25+
—
Typical Enterprise Customer Annual Cost(USD)
$150,000-500,000
—
Base Monthly Cost (100 GB/month)(USD)
$5,000-8,000
—
Base Monthly Cost per Host(USD)
$50/month
—
Custom Metrics Cost(USD per metric/month)
$0.10 per metric
—
Monthly Cost Per Host (Enterprise)(USD)
$25-40
—
Starting Price Per Host(USD/month)
$45-65 per host
—
Starting Annual Cost(USD)
$15,000
—
Starting Monthly Cost(USD)
$500-800
—
Log Ingestion Cost per GB(USD)
$1.20-1.60
—
Typical Monthly Cost (100 hosts)(USD)
$5,000-15,000 (host-based licensing)
—
Time to First Dashboard(minutes)
60-120
—
Time to First Dashboard(days)
30-60 (needs datasource setup)
—
Initial Deployment Time(weeks)
14-28 days
3-5 days
Typical Deployment Time(hours)
2-4 weeks
—
Average Time to Value(days)
< 1 day
—
Log Management
Requires Loki plugin
—
APM Capabilities
Plugin-based with limited support
—
On-Call Scheduling Features(null)
Requires integration (OnCall)
—
Data Sources Supported(integrations)
90+ (Prometheus, Elasticsearch, Datadog, etc.)
—
Built-in Alerting Capabilities(null)
Basic (via connected datasources)
—
Show 22 more attributes
AI-Powered Anomaly Detection Accuracy(percent)
Not available
85%
Alert Management Channels(count)
50+
40+
Log Search Capability
Basic text filtering
—
APM Features
Limited (requires integration with APM platforms)
—
Visualization Chart Types(count)
15+
—
Native Data Source Integrations(count)
470+ integrations
—
Full-Text Log Indexing
No (time-series focused)
—
Built-in Machine Learning Models(count)
3-5 (via plugins)
—
Native APM Integration
No (plugin-based)
—
APM Language Support(languages)
5+ (requires manual agent setup)
—
Dashboard Customization Level
Unlimited panels, custom plugins, full code access
—
AI/ML Anomaly Detection
Basic threshold-based alerts only
—
Out-of-Box Integrations(count)
500+
—
Automatic Code Instrumentation
Native zero-code instrumentation
—
Native Kubernetes Support
Built-in Kubernetes Observer
—
Third-Party Integrations(integrations)
450+ integrations
—
Data Retention (Standard Plan)(days)
35 days
—
Kubernetes/Container Auto-Discovery(capability)
Native, automatic service mapping
—
Native Integrations Available(count)
350+
—
Log Management Included(null)
Available but often separate
—
Data Retention Standard(days)
365 days
—
Infrastructure Monitoring Breadth(coverage %)
Full-stack (apps, infra, K8s, serverless, on-prem)
—
Community Size(millions of users)
500K+ users
—
GitHub Stars (Community Adoption)(count)
58,000+ (as of 2026)
—
Grafana/Dynatrace Community Size(thousands of members)
500K+ monthly active users
100K+ enterprise customers
GitHub Stars (Community Traction)(thousands)
18.5k stars
—
Community Size(members)
5,000+ (proprietary)
—
Mean Time to Response (MTTR) Improvement(percent)
Not measured
—
Alert Fatigue Reduction(percent)
Alert grouping available
—
Default Data Retention(days)
None (external source dependent)
—
Memory Usage (Typical Instance)(MB)
200-500
—
Memory Footprint (Minimal Setup)(MB)
~200 MB
—
Show 14 more attributes
Minimum Dashboard Refresh Interval(seconds)
0.001 seconds (milliseconds)
—
Log Query Response Time(milliseconds)
5,000-10,000 (Loki)
—
Event Ingestion Rate (Single Indexer)(events/sec)
1,000-2,000
—
Real-Time Dashboard Latency(milliseconds)
50-500
—
Minimum Deployment Memory Requirement(MB)
500 MB
2000+ MB (full SaaS service)
Minimum Dashboard Refresh Rate(seconds)
5-10 seconds (typical)
—
Average Search Query Time (1GB dataset)(seconds)
0.5-2 seconds
—
Time to Deploy Dashboard(minutes)
5-10 minutes with templates
—
Free Tier Data Retention(days)
15 days
—
Average Deployment Time(seconds)
3 hours
—
Average Time to Root Cause (MTTR)(minutes)
15-30 (with Davis AI)
—
Mean Time to Resolution (MTTR)(minutes reduction)
45% faster than legacy APM
—
Query Performance on 1TB Index(milliseconds)
< 500ms (P95)
—
Average Time to Root Cause(minutes)
2.5 minutes
—
Customer Retention Rate(%)
94%
—
Gartner Peer Reviews Score(out of 5.0)
4.7/5.0 (1,800+ reviews)
—
Query Language Learning Curve(complexity rating)
2-4 (depends on datasource type)
—
Dashboard Creation Time(minutes)
5-10 minutes
—
User Onboarding Time(hours)
7-14 days (JSON, API, plugin config)
—
Learning Curve(difficulty rating)
1-2 months
—
Standalone Operation
No—requires external datasource
—
Base Pricing (Annual, 100 hosts)(USD)
$0 (self-hosted)
$50,000
Total Cost of Ownership (Year 1)(USD)
$8,000-$24,000+
—
Total Cost of Ownership (3-year, 500GB/month ingestion)(USD)
$360,000 (6,000 GB × $3/GB × 3 years + support)
—
Starting Annual Price(USD)
$52,500
—
Monthly Pricing (Small Organization)(USD)
$12,000-20,000
—
Supported Technologies (Languages/Frameworks)(count)
300+ via integrations
100+ with native agents
Data Source Support(integrations)
80+
—
Supported Programming Languages(count)
50+ languages
—
Supported Technologies(integrations)
650+ out-of-box
—
Required IT Staff for 10,000 hosts(FTE)
3-5 FTE
0.5-1 FTE
Infrastructure Setup Complexity(DevOps hours)
20-40 hours (minimal)
—
Required Infrastructure Team Size (100 users)(FTEs)
0.25 (mostly monitoring)
—
Commercial Support Cost(USD/month)
$25-150+ per user
—
Open Source License Type
AGPL v3 (user-friendly for most use cases)
—
Query Language Complexity
PromQL, SQL, or source-native language
—
Built-in Alerting Rules(feature)
Visualization only (external routing required)
—
Notification Channels(integrations)
50+
—
Minimum Monthly Cost (Small Org)(USD)
$0 (open-source) or $9 (Grafana Cloud)
—
Monthly Platform Cost (100GB/month ingestion)(USD)
$2,500-$5,000
—
Data Source Integrations Available(count)
450+ pre-built plugins
—
Supported APM Frameworks(count)
100+ via plugins (manual integration required)
—
Setup Time for Basic Monitoring(days)
2-5 days (infrastructure knowledge required)
—
Time to First Dashboard Creation(minutes)
5-10 (intuitive interface)
—
AI Anomaly Detection
Limited; basic alerting rules, ML via separate module
Proactive Davis AI engine
AI Root Cause Analysis(null)
Advanced Davis AI with causality mapping
—
AI-Powered Root Cause Analysis(native capability)
Davis AI included
—
Enterprise Support SLA
Community support; no guaranteed SLA
—
Data Retention (Free Tier)(months)
Unlimited (self-hosted) or 15 days (Grafana Cloud free)
—
Metric Data Retention(days)
15 days
—
Trace Data Retention(days)
8 days
—
Metrics Data Retention(days)
15 days
—
Max Data Retention (free tier)(days)
15 days
—
Show 3 more attributes
Data Retention (Default)(months)
15-30 days (configurable)
—
Log Retention (Standard)(days)
5 days
—
Standard Data Retention(months)
15 months
—
User Seats Included (Starter)(seats)
Unlimited on self-hosted; 1 on Grafana Cloud free
—
Maximum Dashboard Rows Per Organization(count)
Unlimited
—
Ingest Rate (Typical)(events per second)
100,000+ EPS per cluster
—
Row-Level Security (RLS)
Supported via RBAC and data source filtering
—
Enterprise Security Features(count)
Basic RBAC, no SIEM module
—
Enterprise Compliance(certifications)
SOC 2, ISO 27001
—
Built-In Machine Learning Algorithms(count)
3-5 (basic anomaly detection)
—
Minimum RAM Requirement (Self-Hosted)(GB)
<2
—
Deployment Flexibility
Self-hosted, Docker, K8s, multi-cloud, air-gapped
SaaS only (limited on-premises for enterprise)
Deployment Options
Self-hosted, Docker, Kubernetes, Cloud
—
GitHub Stars(stars)
56,000
—
Initial Setup Time(minutes)
15-30
—
SQL Query Support
Limited—primarily Prometheus-style queries
—
Built-in APM
No, requires external tools
—
AI/ML Analytics
No native features
—
Time to Production Deployment(days)
30-240 minutes (varies)
—
Self-Hosted Deployment
Fully supported
—
Automatic Instrumentation Coverage(technologies)
Not applicable (requires manual integration)
650+ supported technologies
AI-Powered Anomaly Detection(built-in)
Not included (requires manual alerting rules)
Yes (Davis AI engine)
Community Dashboard Templates(dashboards)
10,000+ community-created dashboards
Curated pre-built dashboards (proprietary)
Native Integrations(count)
700+ pre-built integrations
—
Number of Out-of-Box Integrations(integrations)
500+ (incl. Slack, Splunk, Okta)
—
Advanced Statistical Functions(count)
Basic math and aggregation functions
—
Full-Text Search Optimization
Basic text filters
—
Supported Technology Integrations(count)
600+
—
Typical Implementation Timeline(days)
6-12 weeks
—
Free Trial Duration(days)
14 days (limited)
—
Setup Time for Multi-Service Environment(days)
2-4 days (automatic)
—
Free Trial Period(days)
15 days
—
Infrastructure Monitoring Depth(scope level)
Full-stack (hosts, containers, DBs, k8s)
—
API Request Rate Limit(requests per minute)
1,000 req/min
—
Implementation Timeline(weeks)
2-4 weeks
—
Code-Level Instrumentation Depth(null)
Full bytecode line-level
—
Automatic Anomaly Detection(null)
ML-based automatic baselines
—
Typical Implementation Time(weeks)
3 weeks
—
Included Infrastructure Metrics(metrics per host)
70 metrics
—
Code-Level Profiling Capability
Continuous profiling with memory/CPU/I/O analysis
—
Minimum Contract Term(months)
12-month commitment
—
Root Cause Analysis Technology
AI-driven Davis engine with code-level insights
—
Average MTTR Improvement(percent reduction)
60% reduction
—
Mean Time to Resolution (MTTR) Improvement(percentage reduction)
40-60% reduction with AI
—
Supported Programming Languages (APM)(languages)
95+ languages
—
User Satisfaction Score (G2 Reviews)(out of 5.0)
4.5 stars (1,200+ reviews)
—
APM Code-Level Detail(null)
Full transaction tracing
—
G2 Customer Satisfaction Rating (2024)(stars)
4.6/5.0
—
Customer Satisfaction (NPS)(score)
68 NPS
—
G2 Review Count (2024)(reviews)
1,200+
—
API Complexity(learning effort)
Simplified REST API with UI-first approach
—
Setup Time(minutes)
14-28 days
—
AI Root Cause Analysis Capability(dependency hops)
Automatic detection up to 4+ hops
—
Typical Enterprise Annual Cost (1000 hosts)(USD)
$540K-780K
—
Time to First Production Insight(days)
3-7 days
—
Query Language Flexibility(flexibility score)
Limited to predefined queries and dashboards
—
Community Size & Resources(active contributors)
~10,000 community members
—
Number of Pre-built Integrations(count)
600+
—
Supported Data Types(types)
Logs, metrics, traces, user sessions, synthetics
—
Data Retention Default(months)
15 months
—
Kubernetes Cluster Support(native capability)
Full native support with auto-discovery
—
Deployment Models(count)
SaaS, on-premise, hybrid
—
AI-Driven Root Cause Automation(% of issues auto-detected)
~75-85% with Davis AI
—
Mobile App Monitoring Support
Limited third-party integration only
—
Typical Enterprise Customer Size(employees)
5,000+ (enterprise focus)
—
AI Root Cause Analysis Sophistication(capability level)
Advanced (causal, predictive, auto-remediation)
—
Ideal Organization Size(engineers)
500+ engineers
—
Time to First Alert(minutes)
2-5 minutes (after setup)
—
Pros & Cons
10 pros·6 cons across both
Grafana
+5-3
Pros
- Free and open-source with no per-user licensing costs
- Supports 800+ data sources including Prometheus, Elasticsearch, Influxdb, Loki, and Jaeger
- Highly customizable dashboards with extensive plugin ecosystem (400+ official plugins)
- Large active community with extensive documentation and tutorials
- Flexible alert routing and notification channels (Slack, PagerDuty, Opsgenie, etc.)
Cons
- Requires manual setup of data collection agents and infrastructure
- Limited native anomaly detection and AI-powered root cause analysis capabilities
- Operational overhead of maintaining monitoring infrastructure across team
Dynatrace
+5-3
Pros
- Automatic instrumentation for applications without code changes (OneAgent covers 100+ technologies)
- AI-powered anomaly detection (Davis AI) identifies issues before impact with 85% accuracy
- Full-stack visibility from infrastructure through application to user experience (Real User Monitoring)
- Native support for containerized environments with automatic Kubernetes monitoring
- Minimal setup time; typically observing applications within 3-5 days versus 2-4 weeks for Grafana
Cons
- Significantly higher cost; typically $500K-$2M annually for enterprise deployments
- Limited customization compared to open-source alternatives; locked into vendor features
- Vendor lock-in risk; migrating away requires substantial re-architecture
Frequently Asked Questions
5 questions
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.
Resources & Learn More
Curated sources to dive deeper
Where to Buy
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Wikipedia
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