Prometheus vs Datadog – What’s the Difference ? (Pros and Cons). In this post we introduce two monitoring solutions. First one is Prometheus. A free event monitoring and notification application. What it does, it record’s real time metrics to a time series database built using an HTTP upload model with flexible queries and real time alerts. Moreover, a prolog style query language is used for deductive databases. Known for deduction methods from type logic. Additionally, it consists of axioms and inference rules. Second solution is Datadog. Your infrastructure monitoring happens in one place and you know right away when critical changes are happening on your alerting platform. What is more you check metrics, or network endpoints, plus more.
In this article, I explain about these two tools are and how they work. Following, there is introduction to it’s key features, along with the pros and cons. At the end, I illustrate their differences.
Shall we start with Prometheus vs Datadog – What’s the Difference ?
What is Prometheus?
Additionally, it is designed to be horizontally scalable and is often used in combination with other tools, such as Grafana, to visualize and analyze the metrics it collects. It has a powerful query language and is used to monitor the performance and availability of a wide range of systems, including servers, databases, and applications.
Why use Prometheus?
- Powerful query language and API, which makes it easy to retrieve and process the metrics it collects.
- Free and open source, making it an attractive option for those who prefer open source solutions.
- Large and active community with a wide range of integrations and tools available.
- Designed to be horizontally scalable, so it easily handles large amounts of data from multiple sources.
- Simple and flexible data model that supports multi dimensional metrics and labels.
How does Prometheus work?
- Firstly, the server collects (downloads) metric data from various sources called “exports”. Exports provide metrics data in a specific format that Prometheus scrape, such as a specific HTTP endpoint.
- Secondly, the server stores the collected data in a time series database.
- Thirdly, users query the Prometheus server to retrieve specific metrics or perform aggregate calculations (e.g. average, sum, ratio).
- Fourthly, can be configured to trigger alerts when certain thresholds are crossed based on collected metrics. These notifications are sent to various notification channels, such as email or Slack.
- Fifthly, users create custom dashboards or charts to visualize metrics using Prometheus Query Language (PromQL).
Worth noting that it includes a web interface for visualising and exploring the collected time series data.
In the main, it has a powerful query language for processing and analysing collected time series data.
Scaping is extracting metrics from monitored targets by collecting HTTP endpoint metrics from those targets.
A built in notification system that sends notifications based on the evaluation of PromQL expressions.
Pros and cons of Prometheus
- The program is surprisingly responsive, and my data preparation and organization is reflected with good results.
- Basically Prometheus can also be combined with Grafana to display beautiful counters and create complex alert rules using Alert manager.
- Best cloud native and metrics based tool support and best monitoring tool.
- TSDB- Time Series DataBase and Pull based tool.
- Price difference between its competitors, since this may be the most expensive.
- Creating alerts is somewhat complex, if its language has not been learned correctly.
- Query language (PromQL) is alsosomewhere complex while building advanced dashboard.
Now it is time for the second solution in the article Prometheus vs Datadog – What’s the Difference ?
What is Datadog?
Generally, Datadog is a monitoring and analysis tool for information technology (IT) and DevOps teams, that provides performance metrics and event monitoring for infrastructure and cloud services. Also, software monitor services such as servers, databases, and tools. Generally, monitoring software is available as a Software as a Service (SaaS) deployment.
Why use Datadog?
The most important use cases that have been found are presented below:
Analyses and visualizes data – has a set of tools for collecting, storing, and analysing data and creates dashboards and charts to visualize data. In turn, this helps you gain insight into system performance and usage.
How does Datadog work?
Data is analysed – Provides a set of tools for analysing and processing the collected data. These tools include a powerful query language, dashboard builders, and integration with third party visualization tools.
Integration – Datadog integrates with a wide range of tools and services, including cloud platforms, application performance management (APM) tools, and logging tools. In effect, it allows monitoring and analytics data to be centralized and consolidated.
Features of Datadog
Tracing and APM
The application performance monitoring capabilities available with Datadog break down the barriers between simple monitoring and control. In essence, management starts with detailed monitoring of transactions. Common cases happen on the front end, Datadog is aware of everything all the way to the back end and any database queries it may have triggered.
After pulling too many strings with an agent and an intuitive APM system, it’s useful to have a window pane onto which all results are projected. In turn, it is for this logical summit that Datadog boasts a fully customizable dashboard. Overall, this feature provides a level of data visibility that most data visualization platforms only dream about.
Surely, customizable Datadog dashboards allow you to focus on the logs and metrics you really need. Yes, sometimes it’s worth looking at user reports. But with such enormous collectible power, it’s easy to get caught up in the trend’s colourful graphic representations.
The Datadog agent
If we were to compare the process of acquiring data in all possible environments to fishing, agents would be the components of a hook and a bait. Every pipeline starts with a Datadog agent configured to receive logs from over 400 integrations. Once you learn how to get the agent, there are few nodes from which you can’t extract logs.
In sum, Datadog’s dedicated training gives you control over any framework or environment you want to build your network into.
Pros and cons of Datadog
- Long time history to compare over time.
- Combined with New Relic and OpsGenie you have all the alerts you need.
- Integrations with other tools like PagerDuty, Slack and AWS.
- The dashboard is easy to customize and understand for our organization to consume various site metrics.
- Customer support is helpful and responsive. Generally helps with workarounds to any issues.
- Needs to be woven into application’s code which creates dependencies.
- There has to be an easier way to create new dashboards and a way to implement them as code.
- Configuration of the agent is generally done via a config file which is a pro and a con. So, it would be nicer to have some UI to configure various agent options.
- Sometimes the graphics are a little bit confusing.
We have reached the main part of the article Prometheus vs Datadog – What’s the Difference ?
Prometheus vs Datadog - Key Differences
As you already know, both are used as monitoring tools, but there are differences. On one side, Datadog is a performance monitoring tool that focuses on and provides every detail about your infrastructure. On the other Prometheus is used as a monitoring tool without any reliance on distributed storage.
Here are the main differences that make the two of them unique.
Use Prometheus to track time series in Kubernetes. However, Datadog is a generic APM that monitors any infrastructure or application, but it is not designed for creative monitoring. In Datadog, you see the interface, backend, and business intelligence on one screen, Opposite to Prometheus, which is difficult.
Both products use third party plugins to add additional features and use them regularly. However, Prometheus offers a bit more third party plugins compared to Datadog. Some of them are: Aerospike, Druid, and CouchDB.
Importantly, you don’t have to pay anything to use Prometheus. However, if you prefer the SaaS option provided by Metricfire, you have to pay. That’s why there are 7 Metricfire service plans, the cheapest plan is $85/month when billed annually. This is a basic plan that allows you to define 10 alert conditions. The highest plan is a customized service with no fixed price. The next premium plan costs £3,849 per month billed annually and entitles you to 250 notifications.
Well ,the Datadog has 12 separately priced modules, each with its own pricing structure. In addition to the free infrastructure plan, all of these versions include unlimited alerts. As an example of Datadog pricing, the Infrastructure Pro plan is $15 per host per month when billed annually. In contrast, Datadog Infrastructure’s Enterprise plan includes AI powered thresholds for notifications and costs $23 per host per month when billed annually.
All Datadog plans come with a 14 day free trial.
Support and Integration
Prometheus supports over 10 languages. Community resources are available for learning about the app, educating users, and troubleshooting issues. Support allows you to use our blog, chat, Slack channel, and mailing list. On the integration side, traditional exports allow third party data to be transferred to Prometheus. Examples include system statistics and Docker, HAProxy, StatsD, and JMX metrics.
Datadog works with a variety of data formats and sources, but it is not a platform tailored to work with a large number of information sources. For example, data types such as .xml, .csv, and .json are not supported. However, it integrates well with other IT security and management tools. Datadog supports API and community extensions for integration into existing IT infrastructure. Available for all major operating systems.
Prometheus is installed on Linux and Windows. Available as a downloadable package from the Prometheus website or GitHub repository. For users who prefer cloud services, Metricfire offers the Hosted Prometheus package. However, this service isn’t free to use, as it includes some setups that already combine elements of storage and Prometheus systems, and is much easier to get started with.
Datadog has only one deployment strategy, the SaaS model. The company runs the software on its servers and provides access to its customers through account creation. Datadog’s cloud delivery system is becoming increasingly popular among software vendors. However, some system administrators don’t like losing control of relying on services residing on remote servers.
Last point of comparison of Prometheus vs Datadog – What’s the Difference ? is installation process. Installing Prometheus initially is a quick process, but if you want to add all the features of Prometheus, things get more complicated. For example, you may need to install third party plugins that complicate the installation process. On the other hand, Datadog includes many built in features to suit your needs. Therefore, no additional third party plugins are required.
Thank you for your time in reading Prometheus vs Datadog – What’s the Difference ? Let’s conclude.
Prometheus vs Datadog – What’s the Difference ? Conclusion
In general, choosing between Prometheus and Datadog depends on your specific needs and use cases. If you are looking for a powerful and customizable monitoring tool that is deployed in a variety of environments, Prometheus is the right choice for you. If you’re looking for an easy to use, all in one monitoring and analytics platform, Datadog might be a better fit.