Datadog and Prometheus Group are key players in the monitoring solutions category. Datadog appears to have the upper hand due to its ease of use and comprehensive integrations, making it suitable for both technical and non-technical users.
Features: Datadog offers shareable dashboards, a wide range of integrations, and robust alert capabilities. Its cloud-based service allows for effortless access to metrics and eliminates infrastructure management. Prometheus provides flexible metrics collection and thrives when integrated with Grafana for visualizations, offering essential monitoring for numerous environments.
Room for Improvement: Datadog could enhance dashboard sharing controls and API consistency while improving pricing transparency. Users have noted the need for better logging and synthetic monitoring. Prometheus lacks native visualization tools, relying on Grafana and has a steep learning curve due to PromQL. Better documentation on exporters is needed for improved usability.
Ease of Deployment and Customer Service: Datadog supports cloud flexibility across public, private, and hybrid environments, known for its responsive customer service. Prometheus, favored in on-premises setups, offers hybrid deployment support but lacks the cloud flexibility of Datadog, though it maintains excellent customer service.
Pricing and ROI: Datadog's pricing tends to be high as usage scales, but its features can justify the cost for larger enterprises. It uses a modular pricing approach. Prometheus, being open-source, is cost-effective with costs arising from hosting and supplementary tools like Grafana. Datadog is noted for operational efficiencies, while Prometheus offers robust features at minimal direct cost.
Using open-source Prometheus saves me money compared to AWS native services.
Prometheus does not offer traditional technical support.
Prometheus is scalable, with a rating of ten out of ten.
Deploying it on multiple instances or using Kubernetes for automatic management has enhanced its stability.
The documentation is adequate, but team members coming into a project could benefit from more guided, interactive tutorials, ideally leveraging real-world data.
There should be a clearer view of the expenses.
The setup cost for Datadog is more than $100.
Prometheus is cost-effective for me as it is free.
Our architecture is written in several languages, and one area where Datadog particularly shines is in providing first-class support for a multitude of programming languages.
The technology itself is generally very useful.
It allows me to save money by avoiding costs associated with AWS native services like CloudWatch or Amazon Prometheus.
Datadog is a comprehensive cloud monitoring platform designed to track performance, availability, and log aggregation for cloud resources like AWS, ECS, and Kubernetes. It offers robust tools for creating dashboards, observing user behavior, alerting, telemetry, security monitoring, and synthetic testing.
Datadog supports full observability across cloud providers and environments, enabling troubleshooting, error detection, and performance analysis to maintain system reliability. It offers detailed visualization of servers, integrates seamlessly with cloud providers like AWS, and provides powerful out-of-the-box dashboards and log analytics. Despite its strengths, users often note the need for better integration with other solutions and improved application-level insights. Common challenges include a complex pricing model, setup difficulties, and navigation issues. Users frequently mention the need for clearer documentation, faster loading times, enhanced error traceability, and better log management.
What are the key features of Datadog?
What benefits and ROI should users look for in reviews?
Datadog is implemented across different industries, from tech companies monitoring cloud applications to finance sectors ensuring transactional systems' performance. E-commerce platforms use Datadog to track and visualize user behavior and system health, while healthcare organizations utilize it for maintaining secure, compliant environments. Every implementation assists teams in customizing monitoring solutions specific to their industry's 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.
We monitor all Application Performance Monitoring (APM) and Observability reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.