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  1. Stackups
  2. DevOps
  3. Monitoring
  4. Monitoring Tools
  5. Prometheus vs collectd

Prometheus vs collectd

OverviewDecisionsComparisonAlternatives

Overview

collectd
collectd
Stacks98
Followers156
Votes5
GitHub Stars3.3K
Forks1.3K
Prometheus
Prometheus
Stacks4.8K
Followers3.8K
Votes239
GitHub Stars61.1K
Forks9.9K

Prometheus vs collectd: What are the differences?

Introduction

In this article, we will explore the key differences between Prometheus and collectd. Both Prometheus and collectd are popular monitoring tools used in the IT industry for collecting and visualizing metrics. However, they differ in several important aspects.

  1. Data storage:

Prometheus stores data in a time series database, allowing users to query and analyze metrics over time. On the other hand, collectd does not have built-in data storage capabilities and requires integration with other databases or monitoring systems for data storage.

  1. Collection method:

Prometheus uses a pull-based model for metric collection, where it actively queries targets at regular intervals to gather metric data. In contrast, collectd uses a push-based model, where it relies on agents installed on target systems to send metric data to a centralized server.

  1. Metrics format:

Prometheus uses its own exposition format called Prometheus exposition format (text-based format), which is simple and human-readable. In contrast, collectd uses a binary format for transmitting metrics, which is more efficient for data transport but not as easily readable by humans.

  1. Monitoring system compatibility:

Prometheus is designed to be a standalone monitoring system and includes its own visualization and alerting capabilities. Collectd, on the other hand, is often used as a data collection agent for other monitoring systems like Graphite or InfluxDB, which handle visualization and alerting.

  1. Scalability and architecture:

Prometheus uses a federated architecture, allowing multiple Prometheus servers to be connected and form a highly scalable monitoring solution. Collectd, on the other hand, does not have native support for federation and may require additional tools or configurations for achieving similar scalability.

  1. Community and ecosystem:

Prometheus has a large and active community, with a wide range of exporters and integrations available. It also has strong integration with Kubernetes for containerized environments. Collectd also has a community and ecosystem, but it may not be as extensive and mature as Prometheus.

In summary, Prometheus and collectd differ in terms of data storage, collection method, metrics format, monitoring system compatibility, scalability and architecture, and community/ecosystem support. Each tool has its own strengths and use cases, so it is important to consider these differences when choosing the right monitoring solution for your specific needs.

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Advice on collectd, Prometheus

Leonardo Henrique da
Leonardo Henrique da

Pleno QA Enginneer at SolarMarket

Dec 8, 2020

Decided

The objective of this work was to develop a system to monitor the materials of a production line using IoT technology. Currently, the process of monitoring and replacing parts depends on manual services. For this, load cells, microcontroller, Broker MQTT, Telegraf, InfluxDB, and Grafana were used. It was implemented in a workflow that had the function of collecting sensor data, storing it in a database, and visualizing it in the form of weight and quantity. With these developed solutions, he hopes to contribute to the logistics area, in the replacement and control of materials.

402k views402k
Comments
Raja Subramaniam
Raja Subramaniam

Aug 27, 2019

Needs adviceonPrometheusPrometheusKubernetesKubernetesSysdigSysdig

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
Susmita
Susmita

Senior SRE at African Bank

Jul 28, 2020

Needs adviceonGrafanaGrafana

Looking for a tool which can be used for mainly dashboard purposes, but here are the main requirements:

  • Must be able to get custom data from AS400,
  • Able to display automation test results,
  • System monitoring / Nginx API,
  • Able to get data from 3rd parties DB.

Grafana is almost solving all the problems, except AS400 and no database to get automation test results.

869k views869k
Comments

Detailed Comparison

collectd
collectd
Prometheus
Prometheus

collectd gathers statistics about the system it is running on and stores this information. Those statistics can then be used to find current performance bottlenecks (i.e. performance analysis) and predict future system load (i.e. capacity planning). Or if you just want pretty graphs of your private server and are fed up with some homegrown solution you're at the right place, too.

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.

fast;simple;integrated;easy to operate
Dimensional data; Powerful queries; Great visualization; Efficient storage; Precise alerting; Simple operation
Statistics
GitHub Stars
3.3K
GitHub Stars
61.1K
GitHub Forks
1.3K
GitHub Forks
9.9K
Stacks
98
Stacks
4.8K
Followers
156
Followers
3.8K
Votes
5
Votes
239
Pros & Cons
Pros
  • 2
    Modular, plugins
  • 2
    Open Source
  • 1
    KISS
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
No integrations available
Grafana
Grafana

What are some alternatives to collectd, Prometheus?

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.

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).

Jaeger

Jaeger

Jaeger, a Distributed Tracing System

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