StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. DevOps
  3. Monitoring
  4. Monitoring Tools
  5. Ambari vs Nagios

Ambari vs Nagios

OverviewDecisionsComparisonAlternatives

Overview

Nagios
Nagios
Stacks811
Followers1.1K
Votes102
GitHub Stars57
Forks38
Ambari
Ambari
Stacks44
Followers74
Votes2

Ambari vs Nagios: What are the differences?

Introduction

In the realm of IT infrastructure monitoring and management, Ambari and Nagios are two popular tools that serve distinct purposes.

  1. Installation and Configuration: Ambari is specifically designed for managing and monitoring Hadoop clusters, providing a user-friendly interface for cluster provisioning. In contrast, Nagios, being a general-purpose monitoring tool, requires separate configurations for each device and service to be monitored, making the setup process more complex and time-consuming.

  2. Alerting Mechanisms: Nagios offers extensive alerting capabilities for system administrators, including notifications via email, SMS, or custom scripts when a predefined threshold is breached. On the other hand, Ambari focuses more on providing real-time insights into the health and performance of Hadoop clusters, with alert integrations being more limited in comparison to Nagios.

  3. Scalability and Flexibility: Ambari is well-suited for scaling and managing large Hadoop clusters, offering automation features for tasks like adding or removing nodes dynamically. Conversely, while Nagios can also handle large infrastructures, its configuration and management may become cumbersome as the scale increases, requiring additional effort to maintain flexibility.

  4. Graphical User Interface (GUI): One notable difference between Ambari and Nagios is the GUI. Ambari provides a comprehensive web-based dashboard that visualizes the entire Hadoop cluster's status and performance metrics in a user-friendly manner. In contrast, Nagios primarily relies on text-based configuration files and a less graphically intuitive interface for monitoring and managing systems.

  5. Community and Support: Nagios boasts a large user community and a wide range of plugins developed by the community to enhance its monitoring capabilities. Ambari, on the other hand, has a more focused community centered around Hadoop ecosystem users, providing specialized support and resources for Hadoop cluster management.

  6. Integration and Ecosystem: Another key difference lies in the integration capabilities of the two tools. While Nagios supports a variety of third-party integrations and plugins for monitoring different technologies and services, Ambari is specifically tailored for the Hadoop ecosystem, offering seamless integration with components like HDFS, YARN, and Hive, thus providing a more cohesive monitoring solution for Hadoop environments.

Summary

In summary, while Ambari excels in managing Hadoop clusters with ease and providing a specialized monitoring solution, Nagios offers more flexibility and customization options for general system monitoring across diverse infrastructures.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Advice on Nagios, Ambari

Matthias
Matthias

Teamlead IT at NanoTemper Technologies

Jun 11, 2020

Decided
  • free open source
  • modern interface and architecture
  • large community
  • extendable I knew Nagios for decades but it was really outdated (by its architecture) at some point. That's why Icinga started first as a fork, not with Icinga2 it is completely built from scratch but backward-compatible with Nagios plugins. Now it has reached a state with which I am confident.
142k views142k
Comments

Detailed Comparison

Nagios
Nagios
Ambari
Ambari

Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.

This project is aimed at making Hadoop management simpler by developing software for provisioning, managing, and monitoring Apache Hadoop clusters. It provides an intuitive, easy-to-use Hadoop management web UI backed by its RESTful APIs.

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
Alerts; Ambari Python Libraries; Automated Kerberizaton; Blueprints; Configurations; Service Dashboards; Metrics
Statistics
GitHub Stars
57
GitHub Stars
-
GitHub Forks
38
GitHub Forks
-
Stacks
811
Stacks
44
Followers
1.1K
Followers
74
Votes
102
Votes
2
Pros & Cons
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
  • 2
    Ease of use
Integrations
No integrations available
Hadoop
Hadoop
Ubuntu
Ubuntu
Debian
Debian

What are some alternatives to Nagios, Ambari?

Grafana

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

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.

Prometheus

Prometheus

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.

Netdata

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

Zabbix

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

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.

Graphite

Graphite

Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand

Lumigo

Lumigo

Lumigo is an observability platform built for developers, unifying distributed tracing with payload data, log management, and real-time metrics to help you deeply understand and troubleshoot your systems.

StatsD

StatsD

It is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).

Jaeger

Jaeger

Jaeger, a Distributed Tracing System

Related Comparisons

GitHub
Bitbucket

Bitbucket vs GitHub vs GitLab

GitHub
Bitbucket

AWS CodeCommit vs Bitbucket vs GitHub

Kubernetes
Rancher

Docker Swarm vs Kubernetes vs Rancher

gulp
Grunt

Grunt vs Webpack vs gulp

Graphite
Kibana

Grafana vs Graphite vs Kibana