Datadog vs Nagios vs Prometheus

Overview

Datadog

Stacks9.8K

Followers8.2K

Votes861

Nagios

Stacks811

Followers1.1K

Votes102

GitHub Stars57

Forks38

Prometheus

Stacks4.8K

Followers3.8K

Votes239

GitHub Stars61.1K

Forks9.9K

Datadog vs Nagios vs Prometheus: What are the differences?

## Introduction
Key differences between Datadog, Nagios, and Prometheus are outlined below.

1. **Monitoring Approach**: Datadog is a cloud-based monitoring and analytics solution that offers a robust set of monitoring capabilities with customizable dashboards and alerts. Nagios, on the other hand, is an open-source monitoring tool that focuses on monitoring the availability of network services and hosts. Prometheus is a CNCF graduated project that uses a pull-based approach for collecting metrics, storing them in a time-series database, and querying them using PromQL.
  
2. **Scalability**: Datadog is a fully managed solution that can easily scale with the growth of your infrastructure, making it suitable for large-scale environments. Nagios requires manual configuration and setup of additional servers for scaling, which can be complex and time-consuming. Prometheus is designed to be highly scalable and can handle large amounts of metrics efficiently, making it a good choice for environments with high metric volumes.

3. **Data Visualization**: Datadog offers a user-friendly interface with pre-built visualizations and customizable dashboards that make it easy to interpret monitoring data at a glance. Nagios, on the other hand, provides basic graphs and status information that require additional configuration for more advanced visualizations. Prometheus also offers basic visualizations but relies on Grafana for more advanced dashboarding capabilities.

4. **Alerting**: Datadog allows users to set up complex alerting rules based on metric thresholds, anomalies, and integrations with other tools for notifications. Nagios supports alerting through email notifications and can be extended through plugins for more customized alerting options. Prometheus has native support for alerting rules but lacks some advanced alerting features found in Datadog.

5. **Monitoring Ecosystem**: Datadog has a comprehensive ecosystem with integrations for a wide range of technologies, making it easy to monitor various components of your infrastructure. Nagios also has a vast library of community-contributed plugins that extend its monitoring capabilities. Prometheus has a growing ecosystem of exporters and integrations, making it suitable for monitoring cloud-native environments.

6. **Cost**: Datadog is a commercial product with tiered pricing based on the number of hosts or containers being monitored, making it more expensive than open-source solutions like Nagios and Prometheus, which are free to use. Nagios and Prometheus are self-hosted solutions, so there are potential costs associated with infrastructure and maintenance.

In Summary, the key differences between Datadog, Nagios, and Prometheus lie in their monitoring approach, scalability, data visualization, alerting capabilities, monitoring ecosystem, and cost.

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Advice on Datadog, Nagios, Prometheus

Raja Subramaniam

Aug 27, 2019

Needs adviceon

Prometheus

Kubernetes

Sysdig

We have Prometheus as a monitoring engine as a part of our stack which contains Kubernetes cluster, container images and other open source tools. Also, I am aware that Sysdig can be integrated with Prometheus but I really wanted to know whether Sysdig or sysdig+prometheus will make better monitoring solution.

779k views779k

Comments

Farzeem Diamond

Software Engineer at IVP

Jul 21, 2020

Needs adviceon

Datadog

Dynatrace

AppDynamics

Hey there! We are looking at Datadog, Dynatrace, AppDynamics, and New Relic as options for our web application monitoring.

Current Environment: .NET Core Web app hosted on Microsoft IIS

Future Environment: Web app will be hosted on Microsoft Azure

Tech Stacks: IIS, RabbitMQ, Redis, Microsoft SQL Server

Requirement: Infra Monitoring, APM, Real - User Monitoring (User activity monitoring i.e., time spent on a page, most active page, etc.), Service Tracing, Root Cause Analysis, and Centralized Log Management.

Please advise on the above. Thanks!

1.59M views1.59M

Comments

Medeti

Jun 27, 2020

Needs adviceon

Amazon EKS

Kubernetes

AWS Elastic Load Balancing (ELB)

We are looking for a centralised monitoring solution for our application deployed on Amazon EKS. We would like to monitor using metrics from Kubernetes, AWS services (NeptuneDB, AWS Elastic Load Balancing (ELB), Amazon EBS, Amazon S3, etc) and application microservice's custom metrics.

We are expected to use around 80 microservices (not replicas). I think a total of 200-250 microservices will be there in the system with 10-12 slave nodes.

We tried Prometheus but it looks like maintenance is a big issue. We need to manage scaling, maintaining the storage, and dealing with multiple exporters and Grafana. I felt this itself needs few dedicated resources (at least 2-3 people) to manage. Not sure if I am thinking in the correct direction. Please confirm.

You mentioned Datadog and Sysdig charges per host. Does it charge per slave node?

1.51M views1.51M

Comments

Detailed Comparison

Datadog	Nagios	Prometheus
Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!	Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.	Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.
14-day Free Trial for an unlimited number of hosts;200+ turn-key integrations for data aggregation;Clean graphs of StatsD and other integrations;Slice and dice graphs and alerts by tags, roles, and more;Easy-to-use search for hosts, metrics, and tags;Alert notifications via e-mail and PagerDuty;Receive alerts on any metric, for a single host or an entire cluster;Full API access in more than 15 languages;Overlay metrics and events across disparate sources;Out-of-the-box and customizable monitoring dashboards;Easy way to compute rates, ratios, averages, or integrals;Sampling intervals of 10 seconds;Mute all alerts with 1 click during upgrades and maintenance;Tools for team collaboration	Monitor your entire IT infrastructure;Spot problems before they occur;Know immediately when problems arise;Share availability data with stakeholders;Detect security breaches;Plan and budget for IT upgrades;Reduce downtime and business losses	Dimensional data; Powerful queries; Great visualization; Efficient storage; Precise alerting; Simple operation
Statistics
GitHub Stars -	GitHub Stars 57	GitHub Stars 61.1K
GitHub Forks -	GitHub Forks 38	GitHub Forks 9.9K
Stacks 9.8K	Stacks 811	Stacks 4.8K
Followers 8.2K	Followers 1.1K	Followers 3.8K
Votes 861	Votes 102	Votes 239
Pros & Cons
Pros 140 Monitoring for many apps (databases, web servers, etc) 107 Easy setup 87 Powerful ui 84 Powerful integrations 70 Great value Cons 20 Expensive 4 No errors exception tracking 2 External Network Goes Down You Wont Be Logging 1 Complicated	Pros 53 It just works 28 The standard 12 Customizable 8 The Most flexible monitoring system 1 Huge stack of free checks/plugins to choose from	Pros 47 Powerful easy to use monitoring 38 Flexible query language 32 Dimensional data model 27 Alerts 23 Active and responsive community Cons 12 Just for metrics 6 Bad UI 6 Needs monitoring to access metrics endpoints 4 Not easy to configure and use 3 Supports only active agents
Integrations
NGINX Google App Engine Apache HTTP Server Java Docker Pingdom MySQL Ruby Python Memcached	No integrations available	Grafana

What are some alternatives to Datadog, Nagios, Prometheus?

New Relic

The world’s best software and DevOps teams rely on New Relic to move faster, make better decisions and create best-in-class digital experiences. If you run software, you need to run New Relic. More than 50% of the Fortune 100 do too.

Grafana

Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.

Kibana

Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.

Raygun

Raygun gives you a window into how users are really experiencing your software applications. Detect, diagnose and resolve issues that are affecting end users with greater speed and accuracy.

AppSignal

AppSignal gives you and your team alerts and detailed metrics about your Ruby, Node.js or Elixir application. Sensible pricing, no aggressive sales & support by developers.

Netdata

Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

AppDynamics

AppDynamics develops application performance management (APM) solutions that deliver problem resolution for highly distributed applications through transaction flow monitoring and deep diagnostics.

Zabbix

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

Sensu

Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.

Stackify

Stackify offers the only developers-friendly innovative cloud based solution that fully integrates application performance management (APM) with error and log. Allowing them to easily monitor, detect and resolve application issues faster

Related Comparisons

Datadog vs Nagios vs Prometheus: What are the differences?

## Introduction
Key differences between Datadog, Nagios, and Prometheus are outlined below.

1. **Monitoring Approach**: Datadog is a cloud-based monitoring and analytics solution that offers a robust set of monitoring capabilities with customizable dashboards and alerts. Nagios, on the other hand, is an open-source monitoring tool that focuses on monitoring the availability of network services and hosts. Prometheus is a CNCF graduated project that uses a pull-based approach for collecting metrics, storing them in a time-series database, and querying them using PromQL.
  
2. **Scalability**: Datadog is a fully managed solution that can easily scale with the growth of your infrastructure, making it suitable for large-scale environments. Nagios requires manual configuration and setup of additional servers for scaling, which can be complex and time-consuming. Prometheus is designed to be highly scalable and can handle large amounts of metrics efficiently, making it a good choice for environments with high metric volumes.

3. **Data Visualization**: Datadog offers a user-friendly interface with pre-built visualizations and customizable dashboards that make it easy to interpret monitoring data at a glance. Nagios, on the other hand, provides basic graphs and status information that require additional configuration for more advanced visualizations. Prometheus also offers basic visualizations but relies on Grafana for more advanced dashboarding capabilities.

4. **Alerting**: Datadog allows users to set up complex alerting rules based on metric thresholds, anomalies, and integrations with other tools for notifications. Nagios supports alerting through email notifications and can be extended through plugins for more customized alerting options. Prometheus has native support for alerting rules but lacks some advanced alerting features found in Datadog.

5. **Monitoring Ecosystem**: Datadog has a comprehensive ecosystem with integrations for a wide range of technologies, making it easy to monitor various components of your infrastructure. Nagios also has a vast library of community-contributed plugins that extend its monitoring capabilities. Prometheus has a growing ecosystem of exporters and integrations, making it suitable for monitoring cloud-native environments.

6. **Cost**: Datadog is a commercial product with tiered pricing based on the number of hosts or containers being monitored, making it more expensive than open-source solutions like Nagios and Prometheus, which are free to use. Nagios and Prometheus are self-hosted solutions, so there are potential costs associated with infrastructure and maintenance.

In Summary, the key differences between Datadog, Nagios, and Prometheus lie in their monitoring approach, scalability, data visualization, alerting capabilities, monitoring ecosystem, and cost.

Datadog vs Nagios vs Prometheus

Overview