Datadog is a fully managed SaaS monitoring platform with built-in alerting and support, while Prometheus is an open-source, self-hosted time-series database requiring manual setup and maintenance. Datadog costs money but requires minimal infrastructure investment, whereas Prometheus is free but demands significant DevOps expertise to operate effectively.
Datadog vs Prometheus — Side-by-side comparison on A Versus B
Choose Datadog if you need a production-ready monitoring solution with minimal setup, managed infrastructure, professional support, and 15-month data retention—ideal for teams prioritizing speed-to-value over cost. Choose Prometheus if you have strong DevOps capabilities, need zero licensing costs, require complete control over your infrastructure, and can maintain open-source components internally—ideal for cost-constrained organizations with technical depth.
Enterprise SaaS monitoring and observability platform with built-in alerting, dashboards, and 600+ integrations.
Open-source time-series database and monitoring system with pull-based metric collection and built-in alerting.
Structured comparison data for Datadog vs Prometheus with 178 attributes.
APM (Application Performance Monitoring)
Default Data Retention (included in pricing)
Base Monthly Pricing (1GB/day ingestion)
Maximum Data Ingestion Per Day (Enterprise)
Typical Enterprise Annual Cost (1000 hosts)
Storage Cost for 1M metrics/sec (1 year)
Datadog vs Prometheus — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for Datadog vs Prometheus.
Is Prometheus suitable for production environments?
Yes, Prometheus is production-ready and used by 62% of enterprises according to CNCF surveys. However, it requires implementing long-term storage solutions (Thanos, Cortex, or Mimir) since native retention is only 15 days. For high-scale deployments (1000+ metrics/sec), add 2-3 engineers to manage infrastructure. Datadog handles this automatically.
What's the total cost of ownership (TCO) difference over 3 years?
For a 50-host deployment: Datadog costs ~$99,000 (3 years at $2,750/month). Prometheus costs $0 in licensing but requires 1.5 FTE ($180,000/year) for setup, maintenance, and upgrades, totaling ~$540,000 over 3 years. Datadog is more cost-effective for teams lacking DevOps depth; Prometheus wins for well-staffed organizations.
Can I migrate from Prometheus to Datadog or vice versa?
Migration from Prometheus to Datadog is straightforward (tools like Telegraf bridge exporters). Reverse migration is difficult—Datadog uses proprietary storage formats. Plan for 1-2 weeks of parallel operation for validation. Most teams keep both systems during transition rather than full cutover.
Which has better performance for high-volume metric ingestion?
Prometheus handles 1-2 million samples/second per instance without sharding. Datadog handles billions of data points across distributed infrastructure. For workloads >5 million samples/sec, Prometheus requires clustering (Thanos or Cortex), while Datadog scales automatically. Datadog is operationally simpler at massive scale.
Do I need both Prometheus and Datadog, or is one sufficient?
Most enterprises choose one or the other based on budget and staffing. Some hybrid approaches use Prometheus for internal monitoring (cost control) and Datadog for customer-facing SLAs (professional support). Only justified if you need on-premises data storage plus cloud observability—rare use case.