Grafana vs Datadog (2026): Features, Pricing & Which to Choose

Grafana and Datadog increasingly compete as observability platforms despite different origins: Grafana evolved from open-source dashboards into a stack incorporating Loki for logs, Tempo for traces, and Mimir or Prometheus for metrics, while Datadog was built as an integrated SaaS service for infrastructure monitoring, APM, logs, RUM, synthetics, and related tools. Grafana offers self-hosted and managed cloud options, strong dashboarding and Kubernetes-native Prometheus support, but can require teams to operate multiple components and query languages; Datadog provides a unified, turnkey interface, mature APM, and extensive integrations, but is SaaS-only and uses layered per-host, per-GB, per-metric, and per-product pricing that can rise significantly with scale. The comparison emphasizes that Grafana may suit organizations seeking deployment control, open-source software, and flexibility, whereas Datadog may fit teams prioritizing ease of setup and centralized vendor management. It also presents OpenObserve as an alternative designed to combine self-hosting or cloud deployment, SQL-based querying across telemetry types, and usage-based pricing without per-host charges.

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