Decision comparison
New Relic vs Dynatrace
New Relic and Dynatrace are both Gartner-recognized leaders in observability, but they serve different priorities. New Relic wins on pricing transparency with its free tier (100GB/month) and open ecosystem of 780+ integrations, making it ideal for cost-conscious teams. Dynatrace excels at automated root cause analysis with its Davis AI engine and Grail data lakehouse, delivering enterprise-grade auto-discovery that reduces manual configuration. The right choice depends on whether your priority is budget flexibility or hands-off AI-driven operations.
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 | Dynatrace |
|---|---|---|
| Best For | Teams wanting transparent usage-based pricing with a generous free tier, 780+ integrations, and strong OpenTelemetry support for cloud-native stacks | Enterprises requiring automated root cause analysis, full-stack auto-discovery with OneAgent, and AI-driven anomaly detection across complex environments |
| Architecture | SaaS-based platform with agent-based instrumentation, NRDB telemetry database, and 780+ quickstart integrations across the full observability stack | Unified platform with OneAgent auto-instrumentation, Grail causal data lakehouse with massively parallel processing, and Smartscape real-time topology mapping |
| Pricing Model | Free tier available, paid plans start at $19/mo per host, additional costs based on usage and features | Dynatrace publishes a per-host rate card against a single annual platform commitment. Foundation & Discovery is $7 per month per host, Infrastructure Monitoring $29 per month per host, and Full-Stack Monitoring $58 per month per 8 GiB host, each also available at $0.01 per hour per host. Other capabilities draw down from the same commitment at published unit rates. There are no per-seat fees, and a 15-day free trial is offered. |
| Ease of Use | Users praise easy setup and real-time performance monitoring, though some report a steep learning curve for advanced NRQL queries and dashboards | Users highlight automated root cause analysis and full-stack visibility, but note a learning curve for custom metrics and advanced configuration |
| Scalability | Unlimited data ingest from all telemetry sources with per-GB pricing, designed to scale across hybrid cloud and on-premises infrastructure | Grail data lakehouse provides indexless schema-on-read storage with massively parallel processing for observability, security, and business data at enterprise scale |
| Community/Support | Named a Gartner Leader in 2025 for Observability Platforms for the 13th consecutive time; 353 reviews with 7.9/10 rating and active community | Named a Gartner Leader in 2025 DEM Magic Quadrant positioned furthest in Vision; 617 reviews with 8.4/10 rating; trusted by Air France-KLM and ADT |
New Relic
- Best For:
- Teams wanting transparent usage-based pricing with a generous free tier, 780+ integrations, and strong OpenTelemetry support for cloud-native stacks
- Architecture:
- SaaS-based platform with agent-based instrumentation, NRDB telemetry database, and 780+ quickstart integrations across the full observability stack
- Pricing Model:
- Free tier available, paid plans start at $19/mo per host, additional costs based on usage and features
- Ease of Use:
- Users praise easy setup and real-time performance monitoring, though some report a steep learning curve for advanced NRQL queries and dashboards
- Scalability:
- Unlimited data ingest from all telemetry sources with per-GB pricing, designed to scale across hybrid cloud and on-premises infrastructure
- Community/Support:
- Named a Gartner Leader in 2025 for Observability Platforms for the 13th consecutive time; 353 reviews with 7.9/10 rating and active community
Dynatrace
- Best For:
- Enterprises requiring automated root cause analysis, full-stack auto-discovery with OneAgent, and AI-driven anomaly detection across complex environments
- Architecture:
- Unified platform with OneAgent auto-instrumentation, Grail causal data lakehouse with massively parallel processing, and Smartscape real-time topology mapping
- Pricing Model:
- Dynatrace publishes a per-host rate card against a single annual platform commitment. Foundation & Discovery is $7 per month per host, Infrastructure Monitoring $29 per month per host, and Full-Stack Monitoring $58 per month per 8 GiB host, each also available at $0.01 per hour per host. Other capabilities draw down from the same commitment at published unit rates. There are no per-seat fees, and a 15-day free trial is offered.
- Ease of Use:
- Users highlight automated root cause analysis and full-stack visibility, but note a learning curve for custom metrics and advanced configuration
- Scalability:
- Grail data lakehouse provides indexless schema-on-read storage with massively parallel processing for observability, security, and business data at enterprise scale
- Community/Support:
- Named a Gartner Leader in 2025 DEM Magic Quadrant positioned furthest in Vision; 617 reviews with 8.4/10 rating; trusted by Air France-KLM and ADT
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 | Dynatrace |
|---|---|---|
| GitHub commits, 90d(Developer adoption) | 303 | 275 |
| GitHub stars(Developer adoption) | 9 | 220 |
| Search interest(Market interest) | 4 | 4 |
| Hacker News mentions, 90d(Community interest) | 1 | 4 |
| npm weekly downloads(Developer adoption) | 894.3k | Not available |
| Product Hunt comments(Community interest) | 1 | Not available |
| Product Hunt reviews(Community interest) | 0 | Not available |
| Product Hunt votes(Community interest) | 16 | Not available |
| PyPI weekly downloads(Developer adoption) | 817.2k | 20.2k |
| Stack Overflow questions(Community interest) | 1.5k | 199 |
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
Dynatrace
September 14, 2026Package vulnerabilities
PyPI · oneagent-sdk@1.5.2.20260107.153442
0 vulnerabilities
across 1 package
Repository security score
Not available
Interface Preview
Dynatrace
Feature Comparison
| Feature | New Relic | Dynatrace |
|---|---|---|
| Application Performance Monitoring | ||
| APM & Distributed Tracing | APM 360 with distributed tracing, code-level diagnostics, and error tracking across services | PurePath captures end-to-end distributed traces with code-level context across the full stack |
| Code Profiling | Low-impact code profiling identifies performance bottlenecks in production environments | Continuous profiling with PurePath technology for timing and code-level context analysis |
| AI/LLM Monitoring | Dedicated AI Monitoring tracks model interactions, token usage, and agent behavior in real time | AI Observability for generative AI applications, LLMs, and agents with deterministic insights |
| Infrastructure & Cloud Monitoring | ||
| Cloud Provider Support | Monitors AWS, Azure, and GCP with dedicated integrations for cloud-native and hybrid environments | Integrates with all major clouds and containers with OneAgent auto-discovery deployment |
| Kubernetes Monitoring | Debug clusters with code-level insights while scaling resources based on demand patterns | Smartscape maps Kubernetes interactions and relationships to infrastructure automatically |
| Network Monitoring | Monitors how networks impact application and service performance across the stack | Network-level telemetry collection as part of the unified full-stack monitoring approach |
| Log Management & Analytics | ||
| Log Collection & Storage | Logs in Context links log data to APM, infrastructure monitoring, and distributed tracing | Grail lakehouse stores logs with indexless schema-on-read for lightning-fast analytics |
| Log Analytics | NRQL query language for deep log analysis with customizable dashboards and alerting | OpenPipeline ingests and enriches log data with AI-powered analytics for troubleshooting |
| Data Retention & Compliance | Enterprise tier offers FedRAMP Moderate and HIPAA eligibility with Data Plus option | Enterprise-grade data privacy and security with scalable volume-based commit pricing |
| Digital Experience & Security | ||
| Real User Monitoring | Browser and mobile monitoring with synthetic testing to pinpoint latency and UX issues | Real-user monitoring with synthetic monitoring and session replays for flawless experiences |
| Session Replay | Session replay with AI that identifies friction points automatically without manual video review | Session replays integrated with digital experience monitoring for end-to-end user journey tracking |
| Application Security | Vulnerability management monitors risks from third-party components across services and workloads | Real-time vulnerability detection and prioritization with automated threat response and forensics |
| AI & Automation | ||
| AI-Powered Root Cause Analysis | AI correlates telemetry across the stack to isolate root causes and reduce MTTR | Davis AI provides deterministic root cause analysis with causal reasoning and anomaly detection |
| AIOps & Alerting | AIOps with automated alerting, detection, correlation, and incident resolution workflows | Agentic AI coordinates teams of agents for predictions, anomaly detection, and automated actions |
| Automation & Integrations | 780+ quickstart integrations with OpenTelemetry support and Slack notification workflows | AppEngine enables custom apps and automations with OpenPipeline for stream data processing |
Application Performance Monitoring
APM & Distributed Tracing
Code Profiling
AI/LLM Monitoring
Infrastructure & Cloud Monitoring
Cloud Provider Support
Kubernetes Monitoring
Network Monitoring
Log Management & Analytics
Log Collection & Storage
Log Analytics
Data Retention & Compliance
Digital Experience & Security
Real User Monitoring
Session Replay
Application Security
AI & Automation
AI-Powered Root Cause Analysis
AIOps & Alerting
Automation & Integrations
Which to choose
New Relic and Dynatrace are both Gartner-recognized leaders in observability, but they serve different priorities. New Relic wins on pricing transparency with its free tier (100GB/month) and open ecosystem of 780+ integrations, making it ideal for cost-conscious teams. Dynatrace excels at automated root cause analysis with its Davis AI engine and Grail data lakehouse, delivering enterprise-grade auto-discovery that reduces manual configuration. The right choice depends on whether your priority is budget flexibility or hands-off AI-driven operations.
Best-fit scenarios
Choose New Relic if:
Choose New Relic when you need transparent, predictable pricing with a generous free tier that includes 100GB of data ingest per month and unlimited basic users. New Relic is the stronger choice for teams that value OpenTelemetry support and want to avoid vendor lock-in with open-source standards. Its 780+ quickstart integrations provide fast onboarding across diverse tech stacks. If your team relies on custom querying with NRQL and wants deep control over dashboards and alerts, New Relic gives you the flexibility to build observability workflows your way.
Choose Dynatrace if:
Choose Dynatrace when your organization runs complex, multi-cloud enterprise environments that demand automated discovery and AI-driven root cause analysis. Dynatrace's OneAgent deploys once per host and continuously collects all relevant metrics without manual configuration. The Grail causal data lakehouse with massively parallel processing handles observability, security, and business data at scale. If your priority is reducing mean time to resolution through deterministic AI insights and you need integrated application security with threat observability, Dynatrace provides the most unified full-stack platform.
These scenarios reflect the available product evidence. Your requirements, existing stack, and team expertise should guide the final decision.
Frequently Asked Questions
How do New Relic and Dynatrace compare on pricing transparency?
New Relic publishes pricing details for its Free, Standard, Pro, and Enterprise editions. Its Free tier includes 100 GB of data ingest per month and unlimited basic users; data ingested beyond the free allowance is listed at $0.40/GB under the original data option. User costs and availability vary by edition, and Enterprise data and full-platform-user pricing are listed as Contact Sales. The supplied evidence does not provide Dynatrace pricing details, so a like-for-like assessment of the two platforms’ pricing transparency is not possible from this evidence alone.
Which platform has better AI-powered root cause analysis?
Dynatrace's Davis AI engine is widely recognized for its deterministic root cause analysis, using causal reasoning rather than correlation to identify problems. It automatically maps dependencies through Smartscape topology and provides anomaly detection without manual rule configuration. New Relic uses AI to correlate telemetry across the entire stack and has introduced an SRE Agent for automated remediation. Both platforms invest heavily in AI capabilities, but Dynatrace's deterministic approach with causal reasoning is more mature for complex enterprise environments where automated root cause detection is the primary requirement.
Can both platforms monitor AI and LLM applications?
Both New Relic and Dynatrace have introduced dedicated AI monitoring capabilities. New Relic provides AI and Agentic Monitoring that tracks model interactions, token usage, and agent behavior in real time, with the ability to control costs across the AI stack automatically. Dynatrace offers AI Observability for generative AI applications, LLMs, and agents, leveraging its deterministic insights for reliable monitoring. Both platforms recognize AI observability as a critical growth area and have positioned their features to monitor the full AI application lifecycle from development through production deployment.
How do the data storage architectures differ between New Relic and Dynatrace?
New Relic stores telemetry data in NRDB (New Relic Database) and provides NRQL as its query language for flexible data exploration across metrics, events, logs, and traces. Dynatrace uses Grail, a causal data lakehouse with massively parallel processing that provides fast, indexless, schema-on-read storage for all data types. Grail contextualizes data relationships automatically using the Smartscape topology map. The key difference is that Dynatrace's Grail is purpose-built to correlate and contextualize data for causal analysis, while New Relic's NRDB offers more direct query flexibility through NRQL for teams comfortable writing custom queries.