Prometheus vs. Datadog: Which is Right for your Business?

Deployment of an application is a significant step for any business. The quicker and better updates you can give to your users, the faster it will be for you to fix issues and introduce new features. With more immediate updates for your application, it is also important to handle the application’s bugs and issues and monitor them. As an entrepreneur, it will require a lot of effort and time, and sometimes it does not even appear to pay off. So either you need to be technically sound about the application, or you need to hire someone who is. 

But there is also a third way to save your time and human resources, which involves automating all those processes. You can automate these processes by using some of the DevOps tools in the market. There are plenty of tools available, and all of them have some unique features and drawbacks. 

In this article, we will be discussing two top competitors in the market, Prometheus and Datadog. If you are using the Kubernetes cluster, then you must have heard about them both. We will be discussing the core features, ease of installation, pricing, user interface, and, finally, third-party integrations.

Feel free to use these links to navigate through the guide:

Prometheus vs. Datadog Comparison Summary

Before going into a detailed discussion of Prometheus vs. Datadog, let’s begin with a quick summary of this overall discussion.

Let us start discussing all the keypoint one by one for both of the tools.

Core features

Core features signify the features used mainly by the user or the features most highlighted by the product owners. Here is a quick overview of the top features offered by the two products.

Prometheus Overview

Prometheus provides time-series data defined by metric names and key/value pairs in a multi-dimensional data model. It uses PromQL, a flexible query language, to leverage this dimensionality and support single server autonomous nodes. It has no reliance on distributed storage, and you can push time series through an intermediary way. Also, you can execute a time series by a pull model via HTTP. If you are not satisfied with one alignment of the User Interface, you change it. 

Accordingly, Prometheus has some options which help you in choosing the correct alignment. You can also discover targets via service discovery or static configuration. Prometheus works well in the perfectly numeric time-series condition, and it also supports multi-dimensional data and its querying, which is one of the most prominent features.

Prometheus is reliable, and its server is standalone; it means it does not depend on any other network storage or server for its services. But the data collected is not perfectly tailored, so you may need to rely on some third-party integration for perfect tailored data. 

Datadog Overview

Datadog provides visibility into your application by monitoring all the problems, bugs, and changes in the website and giving a performance report. You can trace your API request from end to end, view bar charts and graphs for error rates, monitor using auto-generated user-specific feedback, and instrument your code using open source tracing libraries.

It automatically collects and generates log data from all the services, apps, and platforms. You can use that data to manage your customer’s behavior by signing log data in the same context and providing alerts on log data. Using end-to-end user experience visibility, you can see how your application performs in front of users. You can monitor the critical issues with the users, and it also makes it easy to reproduce those bugs.

You can monitor everything from the frontend, backend, and business analytics on one screen. Datadog offers quick troubleshooting of your application issues and informing the team of what they can do without navigating through multiple steps. 


Prometheus is a better choice than Datadog if your application needs to use time-series data extensively. Prometheus also contains some basic features of multi-dimensional data and queries. But if you need advanced features for your application, you should go for  Datadog as it provides an APM, time-series, issue tracking tool. Datadog automatically generates and analyzes your log data, but you will need third-party integration for doing the same in Prometheus.

Ease of Installation

Nobody likes a tool that has a lengthy installation process. It increases the chance of encountering errors and opens you up to a cumbersome process of manually choosing the defaults. Here is an overview of the installation processes of the two products.

Prometheus Installation

Prometheus is reasonably straightforward to install. Owing to its simplicity of use, giants such as Kubernetes also recommend it. As a deployment tool, the basic setup process is quite simple. You have to create a cluster, a config map, and deployment for Prometheus. Prometheus also provides pre-compiled binaries for direct download of the original components.

However, it does not end here. Prometheus is a monitoring tool and provides many features, but it does not offer all of them by itself. For example, if you are more interested in graphs and dashboards, you need to sign up on Grafana and integrate it with Prometheus. For creating a custom alert system, you need to install another third-party tool like AlertManager. Similarly, you need to install a different set of plugins for many other purposes.  Hence, in the end, the complete setup process of Prometheus appears to be quite complicated. 

Datadog Installation

Datadog is easier to install than Prometheus if you are using all of its features. You need to install the Datadog agent as a DaemonSet and configure RBAC permissions. Unlike Prometheus, you do not have to integrate third-party plugins for alert systems or graphs and dashboards. 

Datadog mainly works with the help of a Datadog agent; it is a piece of software installed at the beginning which sends all the data and analytics collected to the Datadog. Although Datadog recommends fully installing the Datadog agent, platforms like Amazon Linux, RedHat, CentOS, Debian, Fedora, SUSE, and Ubuntu also support it as a standalone package known as DogStatsD. 


Prometheus is easier to install than Datadog initially. But if you intend to use the full features of Prometheus, then you will need to install third-party plugins, which makes the installation process complicated. On the other hand, when you install Datadog, it has plenty of features that will meet your essential requirement, and you do not have to install third-party integrations. Hence in installation, Datadog has the edge over Prometheus.


Pricing is one of the essential factors while choosing any product for commercial use. Here is a comparison between the two products on the pricing front.

Prometheus Costs

Prometheus is open source and free to use. However, MetricFire offers business-ready Prometheus as a service. It includes hosted Prometheus, Graphite, and Grafana. Their pricing model starts at $85 per month.

Alternatively, AWS offers managed hosting for Prometheus at very affordable prices. However, the catch here is that AWS does not provide as smooth an experience as MetricFire, and if you are not planning to use other AWS services, MetricFire makes much more sense for your use case.

Datadog Costs

Datadog offers individual prices for each service used. In this case, infrastructure monitoring is the closest category to compare against. Datadog offers a free plan, a $15/month per user plan, and an enterprise plan.


While Prometheus is a free-to-use tool, deploying it for your business can incur costs. If you choose to go with AWS, you can save a lot of money thanks to their super-economical pricing. On the other hand, Datadog costs a minimum of $15 per month for one host and charges individually for each additional service like log management and APM. In this case, Prometheus emerges as a winner in this section. There are reports of cutting down up to 98% costs after switching from DataDog to Prometheus to top it off.

Usability/User Interface

The user interface of a tool affects the ease of use and is responsible for sparking interest among the users. Here is an analysis of the user interface offered by the two platforms.

Prometheus with and without Grafana

As discussed earlier, you need to couple Prometheus with a third-party plugin to view intuitive graphs and charts in one place. Grafana is a great add-on for this purpose. In fact, most of the metric visualization and UI of Prometheus depend on Grafana. Grafana provides a clear visualization for your metrics and provides various sets of tools that help you model the metrics according to your choice. 

Grafana works as a playground for data visualization, where you can create dashboards with various graphics by collecting data from different sources and metrics. The definition of each dashboard varies from the data source. In the case of Prometheus, PromQL helps in describing the way Grafana presents the data.

Without Grafana, Prometheus is limited to its basic visualization capabilities. You can use these to expose a small number of metrics to visualize basic trends. While it is a more straightforward process, it does not yield very useful results. Therefore most organizations choose to couple Prometheus with Grafana wherever possible.

Datadog’s UI

Datadog provides all the metrics in a single screen with various types of tools to modify the metrics provided in the way you like. Datadog also provides the end-to-end visibility of your application. When there is an issue with the backend or frontend, Datadog supplies you with the context for that issue. It also provides you with the facility of enabling browser tests that help you check the user experience with the app. 

Creating tests in Datadog is pretty easy using its synthetic browser features. Using an AI-powered automated browser, Datadaog runs a computerized test every time a significant UI change happens but does not bother you by alarming you on small changes. You can train Datadog according to the human decision-making process and intelligently run tests. 

Datadog helps you fix build errors quickly. It sends you the context of error logs that you will need to troubleshoot the bugs. It also sends the UI the users saw when the bug happened, whether some element had vanished or a server error caused by the backend. All these help you to get to the root of issues faster. On top of the ease of use, these features are in-built in DataDog, and you are not required to install any integrations to use them.


Prometheus provides a very intuitive UI with graphs and charts represented clearly, but all of these features come with the help of Grafana. But in Datadog, you won’t need any extra third-party plugins to create a beautiful user interface. Hence Datadog is a better option if third-party plugins disturb you.


No software can deem itself to be perfect. It always makes sense to give users the flexibility of third-party options to make the most out of your product. Here is a glance at the integration offered in both of these monitoring solutions.

Prometheus Integrations

Prometheus provides a large number of third-party plugins to provide additional facilities with their tool. Some of them are also available on its official GitHub organization. There are various wide varieties of third-party integration like databases, hardware drivers, issue trackers, messaging systems, storage, APIs, alerting, logging, and more. Some of the popular plugins used with Prometheus are Aerospike, Clickhouse, CouchDB, Druid, ElasticSearch, IoTDB, etc.

It is essential to understand that one of the reasons why Prometheus offers a wide variety of plugins is that these plugins make it come alive. Without third-party integrations, it is difficult to make the best use of Prometheus as a monitoring tool.

Datadog Integrations

Datadog offers more than 400 plugins to use. It includes various types of plugins such as automation, messaging, issue tracking, etc. Some of the vital integrations available are Aerospike, Airbrake, Airflow, Active Directory, Cloudflare, ConfigCat, CouchDB, Kubernetes, Fastly, etc. You can check out the complete list of plugins supported by Datadog on their official website

Unlike Prometheus, Datadog offers integrations as an entirely optional add-on. DataDog never forces you to turn to third-party integrations to use them to their fullest extent.


Both of the products provide nearly the same number of plugins in various categories. But Prometheus turns out to beat DataDog by a slight margin. This is due to its heavy reliance on third-party integrations for seamless, regular usage, making it mandatory to house as many integrations as possible.

Prometheus vs. DataDog: Who Wins Out?

Prometheus and Datadog have both turned out to be fully featured tools according to their use cases. While Prometheus offers lower pricing than DataDog, it misses the seamless installation experience and depth in features. Prometheus is a popular choice for the Kubernetes application, while Datadog is considered a comprehensive APM tool. Ultimately, deciding between these should be driven by your specific business requirements.

Wrapping Up

Software is a crucial aspect of most organizations, but users will soon switch tools if the software applications have frequent issues. This is why consistent monitoring of your applications is essential for your business’s success. 

In this blog, we discussed two prominent tools in application monitoring, Prometheus and Datadog. It’s also important to note Scout APM provides rich features for exceptional monitoring of your application and user tracking. You can try Scout free for 14 days, no credit card needed. Sign up now for ScoutAPM to get started!