Amplitude vs New Relic
Detailed side-by-side comparison
Amplitude
FreeAmplitude is a product analytics platform focused on understanding user behavior and optimizing digital product experiences through behavioral analytics, segmentation, and experimentation. It helps product teams make data-driven decisions by tracking how users interact with their applications and identifying opportunities for growth.
Visit AmplitudeNew Relic
FreeNew Relic is a full-stack observability platform designed for developers and DevOps teams to monitor application performance, infrastructure health, and system reliability. It provides real-time insights into the technical health of applications and infrastructure across cloud and on-premises environments.
Visit New RelicFeature Comparison
| Feature | Amplitude | New Relic |
|---|---|---|
| Primary Focus | Product analytics focused on user behavior, engagement patterns, and conversion optimization for product managers and growth teams | Application performance monitoring and infrastructure observability for developers, DevOps, and IT operations teams |
| Analytics & Insights | Behavioral cohort analysis, funnel analysis, retention tracking, and user journey mapping to understand product usage patterns | Performance metrics, error rates, distributed tracing, and anomaly detection to identify technical issues and bottlenecks |
| Real-time Monitoring | Real-time product analytics dashboards showing user engagement, feature adoption, and conversion metrics | Real-time APM with infrastructure monitoring, log analysis, and alerting for system performance and uptime |
| Experimentation | Built-in A/B testing and experimentation platform to test product changes and measure impact on user behavior | No native A/B testing; focuses on monitoring the performance impact of deployments and feature releases |
| Data Analysis Tools | User segmentation, predictive analytics, and custom dashboards for analyzing product metrics and user cohorts | NRQL query language for deep data analysis, custom visualizations, and AI-powered anomaly detection for technical metrics |
| Integration Ecosystem | Integrates with marketing, product, and analytics tools to connect user behavior data with growth strategies | Integrates with 600+ technologies including cloud platforms, CI/CD tools, and modern architectures like Kubernetes and serverless |
Pricing Comparison
Both platforms offer free tiers to get started, but pricing scales based on usage—Amplitude charges based on events and MTUs (monthly tracked users) while New Relic prices based on data ingestion volume. Both can become expensive at scale, though they serve fundamentally different purposes and team needs.
Verdict
Choose Amplitude if...
Choose Amplitude if you're a product manager, product team, or growth team focused on understanding user behavior, optimizing conversion funnels, running experiments, and making data-driven product decisions based on how users engage with your application.
Choose New Relic if...
Choose New Relic if you're a developer, DevOps engineer, or IT operations team needing to monitor application performance, troubleshoot technical issues, ensure system reliability, and gain visibility into your infrastructure and application stack health.
Get Your Free Software Recommendation
Answer a few quick questions and we'll match you with the perfect tools
Select the category that best fits your needs
Pros & Cons
Amplitude
Pros
- + Intuitive interface that's accessible to non-technical users
- + Powerful behavioral analytics with deep user insights
- + Excellent data visualization and customizable dashboards
- + Strong integrations with major marketing and product tools
Cons
- - Steep learning curve for advanced features
- - Can become expensive as data volume scales
- - Initial implementation and setup requires technical resources
New Relic
Pros
- + Comprehensive all-in-one platform eliminating need for multiple monitoring tools
- + Powerful query language (NRQL) for deep data analysis and custom visualizations
- + Excellent support for modern architectures including Kubernetes, containers, and serverless
- + Strong community and extensive documentation with pre-built integrations
Cons
- - Can be expensive at scale with complex pricing based on data ingestion
- - Steep learning curve for advanced features and query capabilities
- - Performance overhead on applications when using intensive instrumentation