DataDog vs Prometheus

DataDog and Prometheus are both popular monitoring solutions used to collect and analyze metrics and monitor the performance of systems, but Prometheus is open source and Datadog is proprietary.

Datadog provides a unified platform for monitoring, troubleshooting, and optimizing modern cloud-native applications and infrastructure. Prometheus is the most popular tool for monitoring time series metricsopen in new window.

So, how to choose between Datadog and Prometheus? This guide provides a head-to-head comparison between both products based on installation complexity, user interface, running costs, and more.

DataDog vs Prometheus

DataDog Key Features

Datadog is a cloud-based monitoring and analytics platform that provides real-time visibility into the performance and behavior of applications, infrastructure, and cloud services.

DataDog allows you to monitor, troubleshoot, and optimize cloud-based applications all the way down to a single line of code or individual user requests.

DataDog Kubernetes

DataDog is most commonly used for cloud-based applications to measure and monitor performance. It provides end-to-end distributed tracing from user devices to backend databases.

DataDog comes with a large collection of pre-built dashboards, for example, the Kubernetes dashboard shows you an overview of pods, nodes, deployments, and more. If you are not satisfied with the results, you can create your own dashboards.

DataDog offers a comprehensive alerting system that can notify you when CPU load is above a certain threshold or when DataDog detects an anomaly in the data.

Prometheus Key Features

Prometheusopen in new window is an open-source monitoring system with flexible query language and real-time alerting. Prometheus collects metrics from various sources and provides real-time visibility into performance and behavior of applications, infrastructure, and services.

Prometheus is widely used in cloud-native environments, and integrates well with other open source tools and platforms, such as Kubernetes and Grafana.


Prometheus does not have a lot of built-in functionality, but it can be easily extended with plugins. If you need an alerting system, you can install AlertManager. If you want rich dashboards with wide variety of charts and widgets, you can install Grafana and use Prometheus as a data source.

Prometheus has its own query language called PromQL that lets users select and aggregate time series data in real time. Learning the language requires some effort and time, but it is worth doing so.

Prometheus also provides a flexible alerting system, enabling organizations to set up rules and receive notifications in real-time when performance thresholds are breached.

Key differences between Datadog and Prometheus

As you can see, there are some similarities between Prometheus and DataDog in terms of supported features and functionality, but there are also significant differences.

DataDog is much more broadly applicable, providing performance monitoring, alert management, and data analysis in one place. Prometheus focuses primarily on collecting and monitoring metrics.

You can start using DataDog immediately after creating an account and installing an agent, but with Prometheus you may need to install additional third-party plug-ins.

In terms of sheer number of features, Datadog is far ahead, but the initial setup can be a bit overwhelming. On the other hand, Prometheus is much easier to get started with and comes with a rich ecosystem of tools and plug-ins that can be added later.

Data collection and storage

DataDog uses a proprietary agent-based approach to collect and route metrics and logs to its cloud platform. It provides automated instrumentation and integration with various frameworks and libraries. DataDog provides its own storage backend and handles data retention and scalability.

Prometheus, being open source, provides a pull-based model where applications and systems expose their metrics in a standardized format. Prometheus scrapes metrics from these endpoints and stores them locally in its time series database.

Prometheus stores metrics in a time series database with unique metric names and key-value pairs for filtering. It uses a pull-based model to collect metrics from target systems and provides a powerful query language and graphical user interface for data analysis and visualization.

Cost and licensing

DataDog is a commercial product with pricing based on usage and features. It offers different pricing tiers and plans based on the number of monitored hosts, metrics, and additional features.

Prometheus, being open source, is free to use and has no direct licensing costs. However, there may be costs associated with hosting, storage, and management the Prometheus infrastructure.

Choosing the right tool

Both products have great features and robust monitoring capabilities, but before making a decision, consider your organization's resources and goals.

You may also want to consider open source DataDog competitors such as Uptrace which can provide the same functionality for a lower price.

Uptrace is an open source APMopen in new window for OpenTelemetry with an intuitive query builder, rich dashboards, automated alerts, and integrations for most languages and frameworks.

Uptrace can process billions of spans on a single server, allowing you to monitor your software at 10x less cost.


The choice between DataDog and Prometheus depends on a number of factors, including specific monitoring requirements, budget, existing infrastructure, and preference for open source or commercial solutions.

DataDog offers a comprehensive, all-in-one solution with additional features and support, while Prometheus offers flexibility, extensibility, and a vibrant open source community.

DataDog is a SaaS-based application with complex pricing tiers and can be quite expensive if you need to monitor lots of resources. As for Prometheus, it is completely free and does not require much maintenance.

Prometheus is a good fit for organizations that need a scalable and open-source monitoring solution for their cloud-native applications, while Datadog is a better choice for organizations that require a more comprehensive and integrated monitoring platform for their entire technology stack.

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