Elastic Observability and Prometheus Group compete in the monitoring and data collection category. Elastic Observability appears to have the upper hand due to its extensive features and ease of deployment, although Prometheus stands out for its metrics collection and cost-effectiveness.
Features: Elastic Observability offers integrated features, scalability, and real-time data analysis via Kibana. It includes exceptional search capabilities, ease of deployment, and comprehensive plugins. Prometheus is known for powerful metrics collection, flexibility, and integration with Grafana, all key aspects for efficient monitoring.
Room for Improvement: Elastic Observability could enhance automation, visualization, and user management controls. It also has potential to grow in predictive analytics and overall ease of use. Prometheus should improve dashboard visualization, query language accessibility, and cluster management while expanding exporter support and documentation.
Ease of Deployment and Customer Service: Elastic Observability is preferred for its simple deployment in hybrid and cloud environments, with strong support and resources for premium users. Prometheus, while flexible across deployments, may require technical expertise for setup and lacks direct vendor support, though it benefits from a strong community.
Pricing and ROI: Elastic Observability, although premium, offers solid ROI by reducing incidents and providing complete visibility, making it competitive for large organizations though costly for small enterprises. Prometheus, being open-source, provides cost-effectiveness without licensing fees, though managed services might incur additional costs.
Using open-source Prometheus saves me money compared to AWS native services.
Elastic support really struggles in complex situations to resolve issues.
Prometheus does not offer traditional technical support.
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.
Prometheus is scalable, with a rating of ten out of ten.
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.
Deploying it on multiple instances or using Kubernetes for automatic management has enhanced its stability.
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.
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.
Prometheus is cost-effective for me as it is free.
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.
It allows me to save money by avoiding costs associated with AWS native services like CloudWatch or Amazon Prometheus.
| Product | Market Share (%) |
|---|---|
| Elastic Observability | 3.9% |
| Prometheus Group | 2.5% |
| Other | 93.6% |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 4 |
| Large Enterprise | 16 |
| Company Size | Count |
|---|---|
| Small Business | 14 |
| Midsize Enterprise | 8 |
| Large Enterprise | 12 |
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.
Prometheus Group specializes in robust monitoring and observability, offering comprehensive data collection, analysis, and visualization across cloud and on-premise environments. Its integration with tools like Python, Java, and Kubernetes enables users to track metrics efficiently.
Prometheus Group provides an open-source, customizable platform focused on flexibility and reliability. Its integration with Grafana enhances data visualization while supporting complex infrastructures for improved productivity. Users rely on its scalable architecture for effective monitoring and observability, aiding performance analytics and alerting. Despite its strengths, challenges with its query language and interface usability persist, along with a need for simpler setup. Enhancing documentation and reporting capabilities remains essential for broader adoption, especially among less technical users.
What are the standout features of Prometheus Group?Prometheus Group is widely implemented across industries like cloud services and IT infrastructure. Organizations monitor infrastructure, applications, and databases, utilizing its capabilities for system scalability and health checks within Azure and Amazon ecosystems. Its integration with Kubernetes supports performance monitoring and ensures reliable data analytics, fostering comprehensive metric tracking.
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