If you're evaluating Datadog and Grafana for your observability stack, pricing is likely your biggest concern—and for good reason. As authorized resellers for both platforms, we've helped 100+ companies make this decision. This guide breaks down real-world pricing with actual numbers, hidden costs, and a calculator to estimate your specific scenario.
Quick Summary: What You'll Pay
Here's the bottom line for typical deployments in 2025:
| Deployment Size | Datadog Annual | Grafana Annual | Annual Savings |
|---|---|---|---|
| Small (20 hosts, 10 services) | $48,000-72,000 | $18,000-28,000 | $30,000-44,000 (60%) |
| Medium (100 hosts, 50 services) | $240,000-420,000 | $84,000-180,000 | $156,000-240,000 (57%) |
| Large (500+ hosts, 200+ services) | $1.2M-2.4M | $420,000-900,000 | $780K-1.5M (60%) |
Key Takeaway
Grafana typically costs 40-70% less than Datadog for equivalent functionality, with savings increasing at scale.
How Datadog Pricing Works in 2025
Datadog uses a complex, multi-dimensional pricing model based on multiple factors. Understanding this is crucial to avoiding bill shock.
1. Infrastructure Monitoring (Hosts)
- Pro Plan: $15 per host per month
- Includes: 150 custom metrics per host
- Additional metrics: $0.05 per custom metric/month
- Enterprise Plan: $23 per host per month
- Includes: 200 custom metrics per host
- Advanced features: RBAC, audit logs, longer retention
- Container Monitoring: $1 per container per hour (billed for concurrent containers)
- Serverless Monitoring: $5 per million invocations
2. APM & Distributed Tracing
- Pro Plan: $31 per host per month
- Includes: 150 indexed spans per host per month
- Ingested spans: $1.70 per million
- Enterprise Plan: $40 per host per month
- Includes: 250 indexed spans per host per month
3. Log Management
- Log Ingestion: $0.10 per GB ingested
- Log Indexing: $1.70-2.55 per million log events indexed (15-day retention)
- Extended Retention: Additional $0.02-0.05 per million events per month
⚠️ Warning: Custom Metric Sprawl
Datadog's custom metric pricing can explode quickly. Each unique tag combination creates a new metric. A single service with 10 endpoints × 4 regions × 3 environments = 120 metrics = $6/month. Scale that to 50 services and you're paying $3,600/month ($43K/year) just for custom metrics.
Learn more about Datadog's official pricing.
How Grafana Cloud Pricing Works in 2025
Grafana uses a simpler, consumption-based model with more predictable costs:
1. Metrics (Prometheus-compatible)
- Free Tier: 10,000 series, 50GB logs, 50GB traces, 3 users
- Pro Plan (Pay-as-you-go):
- Active Series: $8 per 1,000 active series per month
- Samples: $0.20 per million samples ingested
- Enterprise Plan: Custom pricing with 20-30% volume discounts
2. Logs (Loki)
- Ingestion: $0.50 per GB ingested
- Storage: $0.02 per GB per month
3. Traces (Tempo)
- Ingestion: $0.30 per GB ingested
- Storage: $0.02 per GB per month
4. User Seats
- Viewers: Free (unlimited)
- Editors: $8 per user per month
- Admins: $15 per user per month
💡 Grafana Advantage
Grafana's pricing is based on actual data volume, not infrastructure count. This means you can scale services without proportionally increasing costs. With proper OpenTelemetry sampling, you control exactly what you pay for.
Learn more about Grafana Cloud pricing.
Real-World Cost Comparison
Let's compare actual costs for three common scenarios based on our implementation experience:
Scenario 1: Small Startup (20 hosts, 10 microservices)
Environment:
- 20 Kubernetes nodes (hosts)
- 10 microservices with APM
- 2,000 custom metrics
- 50GB logs per day (1.5TB/month)
- 500GB traces per month
- 5 team members need access
Datadog Costs
Grafana Cloud Costs
Scenario 2: Mid-Market Company (100 hosts, 50 microservices)
Environment:
- 100 Kubernetes nodes
- 50 microservices with APM
- 150,000 custom metrics
- 500GB logs per day (15TB/month)
- 5TB traces per month
- 15 database instances
- 20 team members
Datadog Annual Cost
Grafana Annual Cost
When Datadog is Worth the Premium
Despite higher costs, Datadog makes sense when:
Choose Datadog If:
When Grafana Saves You 40-70%
Grafana is the better choice when:
Choose Grafana If:
Migration Cost Analysis: Datadog → Grafana
If you're considering switching from Datadog to Grafana, here's what to expect:
One-Time Migration Costs
Learn more about our platform migration services.
Hidden Costs to Consider
Datadog Hidden Costs
- Custom Metric Sprawl: $50,000-200,000 annually for uncontrolled cardinality
- Log Indexing Creep: $30,000-100,000 annually for unnecessary log indexing
- APM Ingestion Costs: $100,000-300,000 annually for high-volume tracing
- Integration Overhead: $20,000-80,000 annually (each integration adds metrics)
Total Datadog Hidden Costs: $200,000-680,000 annually
Grafana Hidden Costs
- Learning Curve: $10,000-20,000 in training and lost productivity
- Integration Work: $15,000-30,000 for custom data source configuration
- Enterprise Features: $3,588-7,200 annually if needed
Total Grafana Hidden Costs: $28,588-57,200 annually
Net Hidden Cost Difference
Datadog's hidden costs are $171,412-622,800 more expensive annually than Grafana's. This is why many companies are shocked when their Datadog bill hits $500K+.
Calculate Your Specific Costs
Want to know exactly what you'd pay for Datadog vs. Grafana based on your environment?
Get Your Custom Cost Analysis
We'll analyze your current setup and provide detailed cost projections for both platforms—including hidden costs and 3-year TCO.
Frequently Asked Questions
Is Grafana really 40-70% cheaper than Datadog?
Yes, for most deployments. Our analysis of 50+ migrations shows average savings of 52%, with a range of 35-68%. The exact savings depend on your data volumes, custom metrics, and log indexing requirements.
What am I giving up if I choose Grafana over Datadog?
Short answer: Convenience and pre-built integrations.
What Grafana lacks: Out-of-box integrations (you'll configure data sources), AI-powered anomaly detection (Watchdog), unified security monitoring (ASM), infrastructure map visualization, and faster onboarding (2-4 weeks slower).
What Grafana provides: Full observability (metrics, logs, traces), excellent Kubernetes support, OpenTelemetry native, flexible alerting, beautiful dashboards, and vendor independence.
How long does it take to migrate from Datadog to Grafana?
Typical timeline: 8-12 weeks for 50 services
- Planning & architecture: 2 weeks
- OpenTelemetry implementation: 4-6 weeks
- Dashboard/alert migration: 2 weeks
- Training & optimization: 2 weeks
- Parallel running: 4-8 weeks (both platforms active)
Can I use both Datadog and Grafana together?
Yes! Common hybrid approaches include splitting by environment (Production: Datadog, Staging: Grafana), splitting by data type (APM: Datadog, Metrics/Logs: Grafana), or using a phased migration path. Using OpenTelemetry, you can send data to BOTH simultaneously.
How do I control Datadog costs if I'm stuck with it?
Top 5 cost optimization tactics:
- Custom Metric Hygiene: Audit and drop unused metrics, use metric filters
- Log Sampling: Sample DEBUG logs 90%, index only ERROR/WARN at 100%
- APM Trace Sampling: Use head-based or tail-based sampling (1-10%)
- Container Exclusions: Exclude system and short-lived containers
- Retention Optimization: Reduce retention from 15 to 7 days, archive to S3
Expected savings: 30-50% with proper optimization
Conclusion: Which Platform Should You Choose?
The choice between Datadog and Grafana ultimately comes down to your priorities:
Choose Datadog
Best for: Well-funded startups, enterprises with large budgets, teams prioritizing speed over cost
Choose Grafana
Best for: Cost-conscious companies, technical teams, Kubernetes-native architectures
Need Help Deciding?
As authorized resellers for both Datadog and Grafana, we have no bias. We'll help you choose the right platform based on your specific needs, then provide competitive pricing and expert implementation.
About Six Sense Solutions
We're authorized resellers for both Datadog and Grafana, which means we have no bias toward either platform. Our only goal is helping you choose the right observability solution for your specific needs.
We've helped 100+ companies evaluate, implement, and optimize their observability stacks—saving an average of $180K annually.