New Relic and Elastic Observability are two robust tools in the observability market. Elastic Observability seems to have the upper hand due to its comprehensive features and perceived value.
Features: New Relic's notable features include detailed application performance monitoring, strong integration capabilities, and customizable dashboards. Elastic Observability is praised for its scalable architecture, powerful search functionalities, and real-time analytics.
Room for Improvement: New Relic users highlight the need for better cost management tools, more granular alerting options, and improved user learning experience. Elastic Observability feedback indicates a need for improved documentation, a more intuitive learning curve, and better onboarding resources.
Ease of Deployment and Customer Service: New Relic's deployment model is noted for its simplicity and speed, complemented by responsive customer service. Elastic Observability is sometimes seen as complex to deploy but valued for its flexibility.
Pricing and ROI: New Relic users often cite higher costs but recognize a strong return on investment. Elastic Observability is seen as more cost-effective yet still delivers substantial long-term value.
Elastic support really struggles in complex situations to resolve issues.
Issues that could be solved quickly sometimes take longer because they go around in circles.
Elastic Observability seems to have a good scale-out capability.
Elastic Observability is easy in deployment in general for small scale, but when you deploy it at a really large scale, the complexity comes with the customizations.
What is not scalable for us is not on Elastic's side.
There are some bugs that come with each release, but they are keen always to build major versions and minor versions on time, including the CVE vulnerabilities to fix it.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
Elastic Observability is really stable.
For instance, if you have many error logs and want to create a rule with a custom query, such as triggering an alert for five errors in the last hour, all you need to do is open the AI bot, type this question, and it generates an Elastic query for you to use in your alert rules.
It lacked some capabilities when handling on-prem devices, like network observability, package flow analysis, and device performance data on the infrastructure side.
Some areas such as AI Ops still require data scientists to understand machine learning and AI, and it doesn't have a quick win with no-brainer use cases.
Email alert customization is limited; it cannot be tailored much, which makes the system more rigid than optimal.
The license is reasonably priced, however, the VMs where we host the solution are extremely expensive, making the overall cost in the public cloud high.
Elastic Observability is cost-efficient and provides all features in the enterprise license without asset-based licensing.
Observability is actually cheaper compared to logs because you're not indexing huge blobs of text and trying to parse those.
The most valuable feature is the integrated platform that allows customers to start from observability and expand into other areas like security, EDR solutions, etc.
the most valued feature of Elastic is its log analytics capabilities.
All the features that we use, such as monitoring, dashboarding, reporting, the possibility of alerting, and the way we index the data, are important.
Using New Relic speeds up troubleshooting and resolution, giving us a clearer picture of where issues are, thus saving time and effort.
| Product | Market Share (%) |
|---|---|
| New Relic | 5.1% |
| Elastic Observability | 3.9% |
| Other | 91.0% |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 4 |
| Large Enterprise | 16 |
| Company Size | Count |
|---|---|
| Small Business | 65 |
| Midsize Enterprise | 49 |
| Large Enterprise | 60 |
Elastic Observability offers a comprehensive suite for log analytics, application performance monitoring, and machine learning. It integrates seamlessly with platforms like Teams and Slack, enhancing data visualization and scalability for real-time insights.
Elastic Observability is designed to support production environments with features like logging, data collection, and infrastructure tracking. Centralized logging and powerful search functionalities make incident response and performance tracking efficient. Elastic APM and Kibana facilitate detailed data visualization, promoting rapid troubleshooting and effective system performance analysis. Integrated services and extensive connectivity options enhance its role in business and technical decision-making by providing actionable data insights.
What are the most important features of Elastic Observability?Elastic Observability is employed across industries for critical operations, such as in finance for transaction monitoring, in healthcare for secure data management, and in technology for optimizing application performance. Its data-driven approach aids efficient event tracing, supporting diverse industry requirements.
New Relic offers real-time application monitoring and insight into performance bottlenecks. Its customizable dashboards and APM integration provide efficient operational support, while server performance alerts ensure quick issue detection.
New Relic provides comprehensive monitoring of application performance, tracking bottlenecks across databases and front-end components. Users employ it for server and infrastructure monitoring, as well as analyzing key metrics such as CPU and memory usage. The solution's ability to integrate with tools like PagerDuty enhances incident management capabilities. However, users have expressed a need for improvements in query language simplicity, more detailed historical insights, and better mobile app monitoring support.
What are New Relic's most important features?In industries like e-commerce and financial services, New Relic supports application performance monitoring to enhance user experience and system reliability. Organizations leverage its insights for optimizing performance, particularly in server operations and infrastructure management. Its ability to monitor API failures through synthetic monitoring is crucial for maintaining high service levels.
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