Datadog and Prometheus are key competitors in the data monitoring and analytics sector. Datadog seems to have the upper hand due to its comprehensive features and robust customer service, despite its higher pricing.
Features: Datadog offers a hosted solution that eliminates dependency on infrastructure, providing sharable dashboards and seamless integration with various systems. Its centralized data monitoring is supported by easy execution of monitoring actions. Prometheus, as an open-source tool, is praised for its flexibility and customization. It offers strong integration capabilities with a focus on backend systems and is known for its reliability and fast data storage system.
Room for Improvement: Datadog could enhance real-time data capabilities and improve its dashboard sharing controls. Users have expressed concerns about the complexity of its pricing model and a steep learning curve for its query language. Prometheus could benefit from better visualization tools, a more user-friendly interface, and enhanced alerting mechanisms. The addition of comprehensive documentation and more intuitive scaling options are also suggested.
Ease of Deployment and Customer Service: Datadog supports a variety of cloud environments, excelling particularly in public and hybrid cloud settings. It is noted for offering quick and responsive customer service. Prometheus is often used in on-premises and hybrid cloud environments, leveraging its open-source nature. Though both receive positive support feedback, Datadog is distinguished by its proactive customer service, while Prometheus could improve response consistency.
Pricing and ROI: Datadog's pricing is viewed as high, with a complex billing model. However, its comprehensive feature set delivers substantial ROI through efficiency improvements. Users are advised to monitor costs closely. Prometheus provides a cost-effective solution being open source, incurring minimal costs unless integrated into a managed service. Despite offering fewer features than Datadog, its economical nature makes it an attractive choice.
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.
In future updates, I would like to see AI features included in Datadog for monitoring AI spend and usage to make the product more versatile and appealing for the customer.
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.
Product | Market Share (%) |
---|---|
Datadog | 7.2% |
Prometheus Group | 2.5% |
Other | 90.3% |
Company Size | Count |
---|---|
Small Business | 78 |
Midsize Enterprise | 42 |
Large Enterprise | 82 |
Company Size | Count |
---|---|
Small Business | 14 |
Midsize Enterprise | 8 |
Large Enterprise | 12 |
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.
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