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  1. Stackups
  2. DevOps
  3. Monitoring
  4. Monitoring Tools
  5. Ganglia vs RRDtool

Ganglia vs RRDtool

OverviewComparisonAlternatives

Overview

RRDtool
RRDtool
Stacks14
Followers45
Votes6
GitHub Stars1.1K
Forks274
Ganglia
Ganglia
Stacks27
Followers88
Votes0

Ganglia vs RRDtool: What are the differences?

Introduction:

Ganglia and RRDtool are both monitoring tools used in IT environments to collect and store data for performance analysis and visualization. However, they differ in various aspects that make them unique in their own right.

  1. Data Storage Methodology: Ganglia uses a distributed architecture to store data, with data being collected and stored across multiple hosts and aggregated into a central location. On the other hand, RRDtool utilizes round-robin databases (RRDs) to store data in a fixed-size database that can automatically consolidate older data as it grows, making it more suited for long-term data retention.

  2. Data Visualization Capabilities: Ganglia focuses on real-time monitoring and visualization of large-scale clusters and grid computing systems. It provides a web-based interface with features like graphs, metrics, and summary views. In contrast, RRDtool is more oriented towards creating graphs and charts for historical data analysis, with the ability to generate static images that can be embedded in websites or reports.

  3. Customizability: Ganglia offers a flexible and extensible architecture that allows users to develop custom monitoring scripts and plug-ins, enabling them to tailor the tool to specific requirements. In contrast, RRDtool is a standalone tool with limited customization options, primarily focused on data storage and graph creation.

  4. Alerting Mechanisms: Ganglia provides limited support for alerting and notification features, requiring additional third-party tools or integrations to implement comprehensive alerting capabilities. On the other hand, RRDtool does not offer built-in alerting functionalities but can be integrated with other tools or scripts to add alerting mechanisms.

  5. Community Support: Ganglia has a strong open-source community with active development and a wide range of community-contributed plugins and extensions, making it a popular choice for large-scale monitoring environments. In comparison, RRDtool has a smaller community base and fewer extensions, limiting its scalability and adaptability to diverse monitoring needs.

  6. Resource Consumption: Ganglia's distributed architecture can lead to higher resource consumption in terms of network bandwidth and server overhead, especially in large deployments with numerous data sources. In contrast, RRDtool's efficient storage mechanism and compact database files result in lower resource utilization, making it more suitable for resource-constrained environments.

In Summary, Ganglia and RRDtool differ in their data storage methodology, visualization capabilities, customizability, alerting mechanisms, community support, and resource consumption, catering to distinct monitoring requirements in IT environments.

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Detailed Comparison

RRDtool
RRDtool
Ganglia
Ganglia

RRDtool lets you log and analyze the data you gather from all kinds of data-sources (DS). The data analysis part of RRDtool is based on the ability to quickly generate graphical representations of the data values collected over a definable time period.

It is a scalable distributed monitoring system for high-performance computing systems such as clusters and Grids. It is based on a hierarchical design targeted at federations of clusters.

Statistics
GitHub Stars
1.1K
GitHub Stars
-
GitHub Forks
274
GitHub Forks
-
Stacks
14
Stacks
27
Followers
45
Followers
88
Votes
6
Votes
0
Pros & Cons
Pros
  • 6
    Do one thing and do it well
No community feedback yet

What are some alternatives to RRDtool, Ganglia?

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.

Nagios

Nagios

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

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).

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