Decision comparison
New Relic vs Datadog
New Relic and Datadog are both industry-leading observability platforms recognized as Leaders in the Gartner Magic Quadrant for Observability Platforms. We see the core differentiator in their pricing philosophy: New Relic uses per-GB data ingest pricing with generous free-tier data allowances, making costs more predictable as infrastructure scales. Datadog uses multi-dimensional per-host pricing that gives teams granular control but can escalate quickly in large Kubernetes environments with ephemeral pods. For teams prioritizing OpenTelemetry adoption and vendor flexibility, New Relic's first-class OTel-native support provides a stronger migration path. For teams needing deep security monitoring, real-time network visibility, and the broadest set of built-in product modules, Datadog delivers a more comprehensive security and network stack out of the box.
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 | New Relic | Datadog |
|---|---|---|
| Pricing Model | Free tier available, paid plans start at $19/mo per host, additional costs based on usage and features | Free tier available, paid plans start at $0.75 per host per month, additional costs based on usage and features |
| Integration Ecosystem | 780+ quickstart integrations with pre-built observability resources | 600+ technology integrations across cloud providers, DevOps tools, and databases |
| AI Capabilities | AI and Agentic Monitoring with SRE Agent for automated remediation; AI-powered session replay analysis | AIOps for automated alerting, detection, and correlation; AI-powered synthetic test self-maintenance |
| OpenTelemetry Support | First-class OTel-native ingestion for metrics, traces, and logs with open-source instrumentation | Supports OTel ingestion but also promotes proprietary agents and SDKs |
| Free Tier | 100 GB/month free data ingest, unlimited free basic users, no credit card required | Free tier available with limited infrastructure monitoring for up to 5 hosts |
| Best For | Teams wanting unified observability with predictable per-GB pricing and strong open-standards support | Large-scale DevOps teams needing deep real-time dashboards, security monitoring, and multi-cloud network visibility |
New Relic
- Pricing Model:
- Free tier available, paid plans start at $19/mo per host, additional costs based on usage and features
- Integration Ecosystem:
- 780+ quickstart integrations with pre-built observability resources
- AI Capabilities:
- AI and Agentic Monitoring with SRE Agent for automated remediation; AI-powered session replay analysis
- OpenTelemetry Support:
- First-class OTel-native ingestion for metrics, traces, and logs with open-source instrumentation
- Free Tier:
- 100 GB/month free data ingest, unlimited free basic users, no credit card required
- Best For:
- Teams wanting unified observability with predictable per-GB pricing and strong open-standards support
Datadog
- Pricing Model:
- Free tier available, paid plans start at $0.75 per host per month, additional costs based on usage and features
- Integration Ecosystem:
- 600+ technology integrations across cloud providers, DevOps tools, and databases
- AI Capabilities:
- AIOps for automated alerting, detection, and correlation; AI-powered synthetic test self-maintenance
- OpenTelemetry Support:
- Supports OTel ingestion but also promotes proprietary agents and SDKs
- Free Tier:
- Free tier available with limited infrastructure monitoring for up to 5 hosts
- Best For:
- Large-scale DevOps teams needing deep real-time dashboards, security monitoring, and multi-cloud network visibility
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 | New Relic | Datadog |
|---|---|---|
| GitHub commits, 90d(Developer adoption) | 303 | 2.4k |
| GitHub stars(Developer adoption) | 9 | 3,500+ |
| Search interest(Market interest) | 4 | 14 |
| Hacker News mentions, 90d(Community interest) | 1 | 16 |
| npm weekly downloads(Developer adoption) | 894.3k | 7.3M |
| Product Hunt comments(Community interest) | 1 | 1 |
| Product Hunt rating(Community interest) | Unavailable | 5.0/5 |
| Product Hunt reviews(Community interest) | 0 | 13 |
| Product Hunt votes(Community interest) | 16 | 75 |
| PyPI weekly downloads(Developer adoption) | 817.2k | 11.0M |
| Stack Overflow questions(Community interest) | 1.5k | 1.1k |
| Hugging Face downloads(Product adoption) | Not available | 96.6k |
| Hugging Face likes(Product adoption) | Not available | 220 |
As of September 14, 2026 — updated weekly.
Health & risk evidence
Observed public-source checks for mapped package versions and repositories.
New Relic
September 14, 2026Package vulnerabilities
npm · newrelic@14.4.0 · PyPI · newrelic@13.5.0
0 vulnerabilities
across 2 packages
Repository security score
Not available
Datadog
September 14, 2026Package vulnerabilities
PyPI · datadog@0.53.0 · npm · dd-trace@6.16.0
0 vulnerabilities
across 2 packages
Repository security score
github.com/DataDog/datadog-agent
5.9/10
Feature Comparison
| Feature | New Relic | Datadog |
|---|---|---|
| Core Observability | ||
| Application Performance Monitoring | APM 360 with code-level diagnostics, service maps, and business-aligned performance metrics | Full APM with auto-generated service overviews, error-rate graphing, and latency percentile tracking |
| Infrastructure Monitoring | Hybrid visibility across cloud-native and on-premises with Kubernetes cluster insights | Per-host monitoring for cloud and on-prem with AWS, Azure, and GCP native integrations |
| Log Management | Logs in Context with correlation to APM, distributed tracing, and errors inbox | Automated log collection with real-time search, tagging, and correlation without pre-indexing |
| Distributed Tracing & Debugging | ||
| Distributed Tracing | End-to-end trace analysis across distributed systems with automatic context propagation | Request tracing from end to end with open-source tracing library instrumentation support |
| Error Tracking | Full-stack error tracking and triage from a single screen with errors inbox | Error-rate alerts and latency percentile tracking (p95, p99) with APM integration |
| Code Profiling | Low-impact code profiling to identify production performance bottlenecks; CodeStream IDE integration | Continuous profiling available as an add-on module for CPU, memory, and I/O analysis |
| User Experience & Synthetic Monitoring | ||
| Real User Monitoring | Browser and mobile monitoring with session replay and AI-driven friction-point identification | RUM with session replays, frontend performance tracking, and business-impact correlation |
| Synthetic Monitoring | Global traffic simulation for proactive issue identification and SLA management | AI-driven self-maintaining synthetic tests with multi-location performance monitoring |
| Mobile Monitoring | Proactive crash, error, and latency monitoring for mobile applications | Mobile RUM for iOS and Android with crash reporting and network performance tracking |
| AI & Automation | ||
| AI-Powered Insights | Intelligent Observability with SRE Agent for automated remediation; AI monitoring for LLMs and agents | AIOps with automated alerting, incident detection, correlation, and resolution workflows |
| Alerting & Notifications | AIOps-powered alerts with change tracking, customizable dashboards, and notification workflows via Slack | Complex alerting with multi-trigger conditions, PagerDuty and Slack integration, and one-click muting |
| Dashboards | Customizable dashboards with cross-telemetry data visualization and NRQL query support | Real-time interactive dashboards with high-resolution metrics, custom graphs, and code-level customization |
| Security & Compliance | ||
| Security Monitoring | Vulnerability management with prioritized risk assessment using production impact and AI reasoning | Cloud SIEM with real-time threat detection, compliance tools, and security monitoring across infrastructure |
| Compliance & Data Governance | FedRAMP Moderate and HIPAA eligibility with Data Plus; enterprise-grade security and governance | SOC 2, HIPAA, and PCI compliance support; data residency options available for regulated industries |
| API Access | Full platform API with NerdGraph (GraphQL) for programmatic data access and dashboard management | RESTful HTTP API for full data access, custom dashboard uploads, and client library instrumentation |
Core Observability
Application Performance Monitoring
Infrastructure Monitoring
Log Management
Distributed Tracing & Debugging
Distributed Tracing
Error Tracking
Code Profiling
User Experience & Synthetic Monitoring
Real User Monitoring
Synthetic Monitoring
Mobile Monitoring
AI & Automation
AI-Powered Insights
Alerting & Notifications
Dashboards
Security & Compliance
Security Monitoring
Compliance & Data Governance
API Access
Which to choose
New Relic and Datadog are both industry-leading observability platforms recognized as Leaders in the Gartner Magic Quadrant for Observability Platforms. We see the core differentiator in their pricing philosophy: New Relic uses per-GB data ingest pricing with generous free-tier data allowances, making costs more predictable as infrastructure scales. Datadog uses multi-dimensional per-host pricing that gives teams granular control but can escalate quickly in large Kubernetes environments with ephemeral pods. For teams prioritizing OpenTelemetry adoption and vendor flexibility, New Relic's first-class OTel-native support provides a stronger migration path. For teams needing deep security monitoring, real-time network visibility, and the broadest set of built-in product modules, Datadog delivers a more comprehensive security and network stack out of the box.
Best-fit scenarios
Choose New Relic if:
We recommend New Relic for engineering teams that want predictable observability costs as their infrastructure grows. Its per-GB pricing model avoids the per-host cost multiplication that hits hard in containerized and Kubernetes environments. The 100 GB/month free data ingest with unlimited basic users makes it accessible for teams starting their observability journey without upfront commitment. New Relic is also the stronger choice for organizations investing in OpenTelemetry, as it treats OTel as a first-class protocol rather than a secondary ingestion path. Teams that value a unified platform with 50+ capabilities under one experience, from APM and infrastructure to AI monitoring and vulnerability management, will find New Relic's consolidated approach reduces tool sprawl and context-switching overhead.
Choose Datadog if:
We recommend Datadog for DevOps and SRE teams managing complex multi-cloud environments where deep real-time dashboards, network monitoring, and security are top priorities. Datadog's 600+ integrations and its strength in infrastructure monitoring with per-host granularity give teams fine-grained visibility into every layer of their stack. The platform excels at security monitoring with Cloud SIEM, real-time threat detection, and compliance tooling that New Relic cannot match in depth. Datadog's synthetic monitoring with AI-powered self-maintaining tests and its network monitoring across clouds, applications, and devices are particularly valuable for organizations running distributed microservices architectures. Teams already invested in Datadog's ecosystem will benefit from the tight integration between its product modules, though they should carefully model costs before scaling.
These scenarios reflect the available product evidence. Your requirements, existing stack, and team expertise should guide the final decision.
Frequently Asked Questions
How does New Relic's pricing compare to Datadog's for a growing team?
New Relic charges based on data ingested per GB and per-seat user licensing, with no per-host fees. This means costs scale with data volume rather than infrastructure size. Datadog uses multi-dimensional pricing that includes per-host charges for infrastructure and APM, per-GB log ingestion, per-million-event log indexing, and additional costs for custom metrics. For teams running Kubernetes with many ephemeral pods, New Relic's model tends to be more predictable because container count does not directly affect the bill, whereas Datadog's per-host charges can multiply as pods scale.
Which platform has better OpenTelemetry support?
New Relic provides first-class OpenTelemetry-native ingestion, accepting metrics, traces, and logs through open-source instrumentation without requiring proprietary agents. Datadog supports OpenTelemetry ingestion but also promotes its own proprietary agents and SDKs alongside OTel. For teams that want to standardize on OpenTelemetry to avoid vendor lock-in, New Relic offers a more committed open-standards approach, while Datadog provides flexibility to use either OTel or its proprietary instrumentation.
Can both platforms monitor AI applications and LLM-based agents?
Yes, both platforms have invested in AI monitoring capabilities. New Relic offers dedicated AI and Agentic Monitoring that tracks model and agent interactions in real time, letting teams control behavior and token usage across their AI stack. Datadog provides AI observability features through its APM and integration ecosystem. New Relic has positioned AI monitoring as a core platform capability with its Intelligent Observability suite, while Datadog integrates AI monitoring within its broader product modules.
What free tier does each platform offer?
New Relic provides 100 GB of free data ingest per month with unlimited free basic users and no credit card requirement. This covers access to the full platform including APM, infrastructure, logs, and more. Datadog offers a free tier with limited infrastructure monitoring for up to 5 hosts. For teams evaluating both platforms, New Relic's free tier is more generous in terms of data volume and feature access, while Datadog's free tier lets teams test basic infrastructure monitoring at a smaller scale.
Which platform is better for security and compliance use cases?
Datadog has a more mature security monitoring stack with Cloud SIEM for real-time threat detection, compliance monitoring, and security analytics built into the platform. New Relic offers vulnerability management with production-impact-aware prioritization and AI-driven remediation guidance, plus FedRAMP Moderate and HIPAA eligibility through its Data Plus tier. For teams where security monitoring is a primary requirement alongside observability, Datadog offers broader coverage. For teams focused on compliance eligibility and vulnerability management within their observability workflow, New Relic provides strong capabilities.