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

Graphite vs Prometheus

OverviewDecisionsComparisonAlternatives

Overview

Graphite
Graphite
Stacks383
Followers419
Votes42
GitHub Stars6.0K
Forks1.3K
Prometheus
Prometheus
Stacks4.8K
Followers3.8K
Votes239
GitHub Stars61.1K
Forks9.9K

Graphite vs Prometheus: What are the differences?

Introduction

This Markdown code provides a comparison between Graphite and Prometheus, highlighting their key differences. Graphite and Prometheus are both popular monitoring tools used in different ways to collect and visualize metric data. Below are six key differences between these monitoring tools.

  1. Data Model: Graphite uses a hierarchical data model where metrics are organized into a structure resembling a file system, with metrics stored as dotted strings. On the other hand, Prometheus uses a multidimensional data model where metrics are identified by key-value pairs called labels, allowing flexible querying and filtering based on different dimensions.

  2. Data Storage: Graphite stores metric data as time-series in round-robin databases (RRD), which aggregates the data over time intervals. Prometheus, in contrast, uses its custom time-series database with a flexible storage model that allows for more complex queries and retention policies.

  3. Data Collection: Graphite relies on a pull-based approach, where applications or systems push metrics to the Graphite server periodically. Prometheus, however, uses a pull-based approach, where it scrapes metric endpoints exposed by monitored applications or systems at regular intervals, making it more resilient to network failures and scalable when monitoring large environments.

  4. Query Language: Graphite uses its own query language called Graphite Query Language (GQL) for data retrieval and manipulation. GQL supports various wildcard expressions and mathematical operations. In contrast, Prometheus uses a more powerful query language called PromQL (Prometheus Query Language), which provides a rich set of functions, operators, and aggregations to easily explore and analyze metric data.

  5. Alerting: Graphite lacks native alerting capabilities and relies on third-party tools for alerting. Prometheus, on the other hand, includes a built-in alerting system that allows defining alert rules based on custom query expressions, sending notifications to various channels (like email, Slack, PagerDuty) when specific conditions are met.

  6. Ecosystem and Integrations: Graphite has a rich ecosystem of compatible tools and integrations, including Grafana for visualization, Carbon for data forwarding, and many others. Prometheus also has a growing ecosystem and integrations with popular tools like Grafana, Alertmanager, and exporters, which allow for seamless integration with existing monitoring and notification setups.

In summary, Graphite and Prometheus differ in their data models, storage mechanisms, collection methods, query languages, alerting capabilities, and ecosystem/integrations, making them suitable for different monitoring use cases and environments.

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Advice on Graphite, Prometheus

Matt
Matt

Senior Software Engineering Manager at PayIt

May 3, 2021

DecidedonGrafanaGrafanaPrometheusPrometheusKubernetesKubernetes

Grafana and Prometheus together, running on Kubernetes , is a powerful combination. These tools are cloud-native and offer a large community and easy integrations. At PayIt we're using exporting Java application metrics using a Dropwizard metrics exporter, and our Node.js services now use the prom-client npm library to serve metrics.

1.1M views1.1M
Comments
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

Detailed Comparison

Graphite
Graphite
Prometheus
Prometheus

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

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.

carbon - a Twisted daemon that listens for time-series data;whisper - a simple database library for storing time-series data (similar in design to RRD);graphite webapp - A Django webapp that renders graphs on-demand using Cairo
Dimensional data; Powerful queries; Great visualization; Efficient storage; Precise alerting; Simple operation
Statistics
GitHub Stars
6.0K
GitHub Stars
61.1K
GitHub Forks
1.3K
GitHub Forks
9.9K
Stacks
383
Stacks
4.8K
Followers
419
Followers
3.8K
Votes
42
Votes
239
Pros & Cons
Pros
  • 16
    Render any graph
  • 9
    Great functions to apply on timeseries
  • 8
    Well supported integrations
  • 6
    Includes event tracking
  • 3
    Rolling aggregation makes storage managable
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
Sensu
Sensu
Nagios
Nagios
Logstash
Logstash
Windows Server
Windows Server
Netdata
Netdata
Riemann
Riemann
Diamond
Diamond
Telegraf
Telegraf
collectd
collectd
Ganglia
Ganglia
Grafana
Grafana

What are some alternatives to Graphite, 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.

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

Telegraf

Telegraf

It is an agent for collecting, processing, aggregating, and writing metrics. Design goals are to have a minimal memory footprint with a plugin system so that developers in the community can easily add support for collecting metrics.

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