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Prometheus vs Datadog: Comparing Differences & Features [2023]

DevOps teams and security engineers use monitoring tools like Prometheus and Datadog to search for bugs and find any issues that might put an app or the entire IT infrastructure at risk. Better monitoring capabilities and aspects like event monitoring mean users can log data more effectively and engage in data collection leading to data visualization. These actions lead to infrastructure metrics, which allow experts to conduct timely analysis and prevent an app from crashing.

When looking for such a tool, you will inevitably come across Datadog and Prometheus. If they are on your shortlist too, this Prometheus vs. Datadog comparison. We will explore similarities and differences to help you choose the right tool for your needs.

What Is Datadog?

Datadog is an all-encompassing monitoring tool designed to provide a complete view of your infrastructure, regardless of location – on-premises, in the cloud, or in a hybrid environment. This tool unifies logs, metrics, and traces, making it easier to identify, optimize and troubleshoot performance issues.

With Datadog, you can automate the monitoring of your infrastructure, application performance, log management, and observability in real time. This ensures you can manage and maintain your entire tech stack effectively and securely. The tool also uses alerts and anomaly detection, making it an indispensable tool for developers, security engineers, and business owners.

Although there are many other monitoring tools available, Datadog’s full-stack monitoring capabilities and emphasis on end-to-end visibility make it a top choice for businesses seeking a comprehensive observability tool.

Prometheus is not its sole competitor. Read more about the best alternatives to Datadog in our dedicated article.

What Is Prometheus?

Prometheus is an open-source monitoring tool that enables businesses to gain better visibility into their infrastructure and applications. The tool is designed to collect and record metrics from various systems and services and store them as time-series data. This makes it easier for developers to troubleshoot issues and optimize performance.

Prometheus is highly configurable and provides users with a flexible query language to help them visualize and analyze the collected data.

Additionally, the tool offers alerts, making it easier to identify potential issues and take action before they cause significant problems. With Prometheus, businesses can easily monitor their systems, applications, and services, making it a valuable tool for DevOps teams and system administrators.

Overview panel for Prometheus

Datadog vs. Prometheus: Side-by-Side Comparison

Datadog and Prometheus are two popular monitoring tools used by businesses of all sizes to keep an eye on their tech stack’s health and performance. Both tools offer a variety of features designed to automate monitoring, optimize and troubleshoot performance issues, and provide real-time observability.

Further on, we’ll compare Datadog and Prometheus side-by-side, looking at their installation processes, main capabilities, customization options, number of integrations, pricing, and audiences. By the end of this article, you’ll have a better understanding of which tool is best suited for your organization’s monitoring needs.

Key Features Overview

When it comes to monitoring tools like Datadog and Prometheus, it’s important to compare the main products they monitor.

Datadog provides

  • infrastructure monitoring,
  • device monitoring,
  • database monitoring,
  • and cloud workload monitoring features.

In addition to log management and security monitoring. It also has real user monitoring capabilities that enable users to capture the user experience of applications.

In contrast, Prometheus collects real-time metrics and stores them in a time-series database, allowing operators to recognize key-value pairs. It also includes a query language, multi-dimensional data modeling, alert manager, and visualization layer with visualization data.

While both tools have unique features, Datadog puts a significant focus on security and cloud monitoring, making it ideal for organizations that rely heavily on cloud infrastructure.

On the other hand, Prometheus is an open-source tool and the successor of Kubernetes, making it suitable for developers and operators who need a scalable, flexible, and customizable monitoring solution.

In terms of the difference in approaches, Datadog provides an all-encompassing solution for monitoring various aspects of the tech stack, while Prometheus is a more focused tool for monitoring real-time metrics.

In conclusion, the choice between Datadog and Prometheus ultimately depends on the specific needs of the organization. If security and cloud monitoring are a top priority, Datadog may be the better option. However, if real-time metrics and scalability are more important, Prometheus may be the way to go.

Installation and Ease of Use

Both Prometheus and Datadog have different installation and deployment processes. Datadog offers an advantage when it comes to installation as it has a relatively easy deployment process, and users can see the installation process as a simple tool. However, users still need to know how to install the tool via DaemonSet and configure it with RBAC permissions. The installation process does not require the integration of any third-party plugins for dashboards or alerting.

On the other hand, Prometheus’ setup process is simpler compared to Datadog. Users create a cluster, proceed with map configuration, and finish with Prometheus deployment. However, Prometheus has limited visualization capabilities, and users need to install a visualization tool such as Grafana to visualize data fully.

When comparing the installation and ease of use of Datadog and Prometheus, it can be said that Prometheus is easier to install. However, it is valid only if users intend to use some of the features Prometheus offers. If users want to leverage the tool fully, they need to install all the third-party plugins, which can make the installation process more complicated. Overall, both tools offer easy installation and deployment, and users need to select the tool that suits their requirements the most.

Dashboards and Reporting

When it comes to dashboards and reporting, Datadog offers an extensive range of options for visualizing data. With Datadog, users have access to over 450 pre-built integrations, allowing them to create custom dashboards and track their infrastructure, applications, and services in real-time. The tool’s dashboards are highly customizable, with the ability to create widgets, graphs, and alerts to suit specific requirements. Additionally, Datadog offers in-depth reporting features, allowing users to generate detailed reports on performance, uptime, and errors.

On the other hand, Prometheus relies on third-party tools for visualization and reporting, with Grafana being the most commonly used. Although Grafana offers excellent visualization capabilities, it requires additional setup and configuration, which can be time-consuming. Prometheus does offer a basic built-in dashboard, but it lacks the customization options and integrations that Datadog provides. As for reporting, Prometheus offers limited reporting capabilities, requiring users to manually extract and analyze data.

Overall, Datadog has a clear advantage over Prometheus when it comes to dashboards and reporting, with a more user-friendly and comprehensive approach.

Incident Management and Alerting

Incident management and alerting are crucial components of any monitoring tool. When comparing Prometheus vs. Datadog, Datadog has a clear advantage in this regard. Datadog’s ML-based tool, Watchdog, is designed to detect issues in your IT infrastructure and notify you via PagerDuty, email, and Slack. All alerts are specific and provide actionable insights to help fix the issues. Moreover, incidents are stored within Datadog’s system alongside all the log data, metrics, and traces, allowing for easy filtering and viewing.

In contrast, Prometheus has a basic built-in alerting system that requires a third-party integration to be fully functional. AlertManager is often used to achieve this, but it may not offer the same level of flexibility and customization that some users require. Additionally, Prometheus lacks Datadog’s anomaly detection capabilities. While Datadog offers a range of integrations for alerting, including AWS CloudWatch and Azure Monitor, Prometheus users must rely on third-party plugins for this functionality.

In summary, Datadog’s incident management and alerting capabilities are superior to Prometheus, particularly for users who want a comprehensive, all-in-one solution.

Third-Party Integrations

Datadog offers a vast number of integrations, with more than 500 available, including Kubernetes, MySQL, and Docker, among others. The tool offers built-in reports and dashboards for many of these integrations, and users can collect metrics through the entire tech stack.

In contrast, Prometheus relies heavily on third-party integrations and plugins, including Elasticsearch, IoTDB, and Clockhouse, for databases, issue tracking, data storage, APIs, logging, and alerting. Prometheus does not provide out-of-the-box reports for these integrations, and users need to set them up manually. While both tools offer similar numbers of integrations, Datadog edges out Prometheus with its optional add-ons and built-in reports. For example, if you want to integrate Datadog with Splunk, you can use one of their add-ons.

Ultimately, it depends on your specific needs and preferences, but Datadog’s extensive integrations and built-in reports make it a strong contender for DevOps professionals.

Pricing and Support

When it comes to pricing, both Prometheus and Datadog offer a variety of packages depending on your needs.

Prometheus is free and open-source, so it is an excellent choice for small teams or startups on a tight budget. However, there may be hidden costs associated with third-party plugins or integrations, and the cost of maintaining and scaling the infrastructure can add up over time.

Datadog, on the other hand, offers several pricing tiers depending on the features and services you need, starting at $15 per host per month. This base package includes infrastructure monitoring, integrations, and basic security monitoring. More advanced packages include features such as APM, distributed tracing, and log management, with prices ranging from $23 to $36 per host per month. Additionally, Datadog offers a 14-day free trial and a free plan for up to five hosts.

It’s important to note that Datadog is considered to be very expensive, especially at scale. Some users are even taking to X to complain about the “insane” prices, and claim that many organizations are working on migrating away from Datadog entirely.

In terms of support, both Prometheus and Datadog have strong communities and offer extensive documentation and support resources.

Prometheus has the advantage of a large community backing it up and constantly building plugins and offering support.

Datadog, on the other hand, offers 24/7 customer support, a knowledge base, and a community forum. They also offer training and professional services to help you get the most out of their platform.

Both platforms are well-supported, but Datadog’s additional support offerings make it a good choice for larger organizations or those with more complex monitoring needs.

Audience

When it comes to deciding which tool is the best fit for your organization’s monitoring needs, you need to consider the size and complexity of your infrastructure. If you have a small-to-medium infrastructure, Prometheus might be the ideal choice. It is an open-source platform that is easy to use and configure, and its lightweight nature allows it to run on low-resource systems.

On the other hand, if you have a larger infrastructure with a complex tech stack, Datadog might be a better fit. Datadog’s extensive feature set, coupled with its ability to integrate with more than 500 technologies, makes it a powerful tool for monitoring and managing large-scale environments. Additionally, its Machine Learning-based Watchdog feature can help detect and mitigate issues before they become critical problems.

Ultimately, the tool that suits best depends on your organization’s specific needs and infrastructure.

Datadog vs. Prometheus for Metrics Monitoring

Datadog and Prometheus are two popular solutions for metrics monitoring, but they have different approaches and features.

Datadog metrics panel

Datadog metrics

Prometheus metrics panel

Prometheus metrics

Datadog is an all-in-one platform that provides real-time metrics monitoring, visualization, and alerting. With Datadog, users can collect metrics from over 450 different sources, including custom metrics, logs, and traces. The platform has a user-friendly interface and supports more integrations with third-party tools than Prometheus. Additionally, Datadog provides built-in anomaly detection and machine learning capabilities, making it easier for users to identify and troubleshoot issues.

On the other hand, Prometheus is an open-source metrics monitoring system that is popular among DevOps teams. It has a powerful querying language and supports time-series data. Prometheus is highly customizable and can be tailored to specific use cases, making it ideal for organizations with complex monitoring needs. However, setting up Prometheus can be challenging, and it requires more technical expertise than Datadog.

In summary, Datadog is a comprehensive, user-friendly option for metrics monitoring that offers a wide range of integrations and features. Prometheus is an open-source, highly customizable solution that is best suited for experienced DevOps teams with complex monitoring requirements.

Datadog vs. Prometheus for Kubernetes

Datadog Kubernetes dashboard

Datadog Kubernetes

Prometheus Kubernetes dashboard

Prometheus Kubernetes

When it comes to Kubernetes monitoring, both Datadog and Prometheus are popular options.

Datadog provides a comprehensive platform for monitoring Kubernetes clusters, offering automatic discovery and tagging of Kubernetes resources, such as pods, services, and deployments. It also provides pre-built dashboards and alerts for Kubernetes, allowing users to quickly identify and troubleshoot issues. Datadog’s platform is straightforward to set up and integrates seamlessly with other monitoring solutions. However, it can be more expensive than other Kubernetes monitoring options.

Prometheus, on the other hand, has a strong focus on Kubernetes and offers powerful monitoring capabilities tailored specifically for containerized environments. Prometheus uses a pull-based model to collect and store Kubernetes metrics, providing users with fine-grained control over what metrics to collect and how to visualize them. Prometheus also has a large community of developers creating plugins and tools for Kubernetes monitoring. However, Prometheus can have a steeper learning curve and may require more effort to set up compared to other Kubernetes monitoring solutions.

In summary, both Datadog and Prometheus offer robust monitoring capabilities for Kubernetes environments. Datadog provides a simple and comprehensive solution with pre-built dashboards and alerts, while Prometheus offers greater flexibility and control over metrics collection and visualization, but may require more effort to set up.

Before making your choice, check out the best Kubernetes monitoring tools on the market.

Sematext: A Better Alternative to Datadog and Prometheus

Sematext is a comprehensive monitoring solution that offers a wide range of features for DevOps teams. When compared to Datadog and Prometheus, Sematext stands out for its versatility and ease of use across multiple monitoring areas.

In terms of application performance monitoring, Sematext provides real-time monitoring of the entire stack, from the frontend to the backend and the infrastructure. The tool can detect issues and errors in real-time, as well as monitor key metrics such as response time, CPU and memory usage, and more. Sematext also offers extensive log management capabilities, including the ability to aggregate, filter, and search logs across multiple servers and applications.

  • For real user monitoring, Sematext provides a detailed view of user behavior and experience, helping DevOps teams optimize application performance and user satisfaction. The tool offers real-time analytics, session replay, and heatmaps, as well as a customizable dashboard that can be tailored to specific user segments and metrics.
  • Sematext’s server monitoring capabilities enable users to monitor and manage the performance of servers and infrastructure components, including CPU and memory usage, disk space, network traffic, and more. The tool provides real-time alerts and can help identify and troubleshoot issues before they affect the end-user experience.
  • For container and process monitoring, Sematext offers an intuitive and user-friendly dashboard that allows users to monitor container health, resource utilization, and performance metrics. Sematext’s container monitoring capabilities also include support for Kubernetes and Docker Swarm, as well as container orchestration and management tools such as Mesos, Nomad, and Rancher.
  • Sematext’s database monitoring capabilities allow DevOps teams to monitor and manage the performance of databases, including MySQL, PostgreSQL, MongoDB, and Elasticsearch. The tool provides real-time insights into database performance metrics such as query response time, throughput, and latency, and can help identify and troubleshoot issues before they affect the end-user experience.
  • Finally, Sematext’s network monitoring capabilities enable users to monitor and manage network performance, including latency, packet loss, and throughput. The tool provides real-time alerts and can help identify and troubleshoot network issues before they affect the end-user experience.

Overall, Sematext is a powerful and versatile monitoring solution that offers a comprehensive set of features for DevOps teams. With its ease of use, versatility, and extensive capabilities across multiple monitoring areas, Sematext provides a better alternative to Datadog and Prometheus.

Want more details? Check out our page on Sematext vs Datadog.

Prometheus vs. Datadog vs. Sematext: Comparison Table

Feature
Prometheus logo
Prometheus
Datadog logo
Datadog
Sematext logo
Sematext
InstallationOn-premiseBoth SaaS or on-premiseBoth SaaS or on-premise
Main CapabilitiesMetrics collection and alerting, scraping endpointsMetrics, logs, traces, and APMMonitoring, alerting, logging, and tracing across systems, applications, and infrastructures
CustomizationHigh level of customizationLimited customizationHigh level of customization with multiple agents and integrations
PricingOpen-source and free to useMultiple pricing tiers, with the basic tier starting at $15 per month per hostMultiple pricing tiers, with the basic tier starting at $29 per month per host
AudienceMid-size to large enterprises with extensive infrastructureMid-size to large enterprises with diverse data sourcesSmall to large enterprises with complex systems and applications
ProsRobust and highly customizableComprehensive and easy to useAll-in-one solution with high customization and scalability
ConsSteep learning curve and requires technical expertiseExpensive and lacks customizationFewer built-in integrations than other solutions

Note: The features listed are not exhaustive and may not cover all aspects of each tool’s capabilities. The table provides a brief overview and comparison of the tools based on the criteria discussed. As always, it’s important to thoroughly evaluate your organization’s specific needs and requirements before selecting a tool.

Read the extended Sematext vs Datadog comparison for a broader context and better decisions.

Choosing Between Datadog and Prometheus

When choosing between Datadog and Prometheus, it’s important to consider the specific technical requirements and use cases of your organization.

While Datadog excels in infrastructure monitoring and performance measurement, Prometheus shines in event and metric monitoring. Additionally, open-source enthusiasts and users familiar with Apache-based platforms may find Prometheus to be the better option.

However, when considering a comprehensive monitoring solution, it’s worth noting that Sematext provides an alternative that can cover all of these areas and more, with powerful logging capabilities, real user monitoring, and distributed tracing, among other features. With Sematext, organizations can consolidate their monitoring tools and gain a more comprehensive view of their application performance, infrastructure, and user experiences.

In the end, the decision between Datadog, Prometheus, and Sematext will depend on a variety of factors, including technical requirements, budget, and ease of use. However, with the right tools in place, organizations can gain powerful insights into their applications and infrastructure, proactively identify issues before they impact users, and ultimately drive better business outcomes.

Start the Sematext free trial today to see if it fits your needs.

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