Apache Superset vs New Relic
Detailed side-by-side comparison
Apache Superset
FreeApache Superset is an open-source business intelligence and data visualization platform designed for data analysts and engineers to explore data through interactive dashboards and SQL queries. It connects to modern SQL databases and provides 50+ visualization types with no vendor lock-in or licensing costs.
Visit Apache SupersetNew Relic
FreeNew Relic is a comprehensive observability platform that provides real-time monitoring of application performance, infrastructure, and user experience across entire technology stacks. Designed for developers and DevOps teams, it offers full-stack observability with APM, distributed tracing, and AI-powered insights for cloud and on-premises environments.
Visit New RelicFeature Comparison
| Feature | Apache Superset | New Relic |
|---|---|---|
| Primary Use Case | Business intelligence and data visualization for analyzing historical data and creating reports from SQL databases | Real-time application performance monitoring and observability for debugging and optimizing live systems |
| Data Sources | Connects to most SQL-speaking databases and cloud data warehouses for structured data analysis | Collects telemetry data from applications, infrastructure, logs, and 600+ technology integrations through instrumentation |
| Visualization & Dashboards | 50+ pre-built chart types with drag-and-drop dashboard builder focused on business metrics and KPIs | Real-time dashboards with customizable widgets focused on system health, performance metrics, and alerting |
| Query Capabilities | SQL IDE with metadata browser for writing custom queries and creating semantic layers with custom dimensions | NRQL (New Relic Query Language) for querying telemetry data, traces, logs, and metrics in real-time |
| Advanced Analytics | Basic aggregations and filtering with limited predictive analytics; relies on external tools for ML capabilities | AI-powered anomaly detection, error analysis, and automated incident detection for proactive monitoring |
| Security & Access Control | Role-based access control and row-level security for managing data access across teams and departments | User management with role-based access for monitoring data and account-level security controls |
Pricing Comparison
Both tools offer free tiers to start, but Apache Superset remains completely free as open-source software with no per-user fees, while New Relic's costs scale with data ingestion volume and can become expensive for large deployments. New Relic requires ongoing subscription costs, whereas Superset only incurs infrastructure and maintenance expenses.
Verdict
Choose Apache Superset if...
Choose Apache Superset if you need a business intelligence tool for visualizing and analyzing data from SQL databases, want to avoid licensing costs, and have technical resources to maintain an open-source platform.
Choose New Relic if...
Choose New Relic if you need comprehensive application performance monitoring and observability for your technology stack, require real-time system health insights with AI-powered alerting, and want an all-in-one platform for DevOps and development teams.
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
Apache Superset
Pros
- + Completely free and open-source with active community support
- + Highly extensible and customizable to specific needs
- + Supports virtually any SQL database including cloud data warehouses
- + No licensing costs or per-user fees for unlimited scaling
Cons
- - Requires technical expertise for installation and maintenance
- - Limited built-in predictive analytics compared to commercial BI tools
- - UI can feel less polished than enterprise alternatives
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