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  5. Grafana vs Graphite vs StatsD

Grafana vs Graphite vs StatsD

OverviewDecisionsComparisonAlternatives

Overview

StatsD
StatsD
Stacks373
Followers293
Votes31
Graphite
Graphite
Stacks383
Followers419
Votes42
GitHub Stars6.0K
Forks1.3K
Grafana
Grafana
Stacks18.4K
Followers14.6K
Votes415
GitHub Stars70.7K
Forks13.1K

Grafana vs Graphite vs StatsD: What are the differences?

# Introduction
Grafana, Graphite, and StatsD are popular tools used for monitoring and visualizing data in the field of Metrics and Observability.

1. **Data Storage**: Grafana is primarily a visualization tool that retrieves data from various databases and data sources, while Graphite is a time-series database that stores and aggregates metrics data. StatsD is a network daemon that runs in the background and collects metrics from various sources before sending them to a backend service, like Graphite, for storage.
   
2. **Real-Time Visualization**: Grafana allows users to create dynamic, real-time dashboards that update in response to new data. Graphite also offers visualization capabilities but may require additional tools to achieve real-time updates effectively. StatsD, on the other hand, focuses on data collection and forwarding, leaving visualization to other tools like Grafana.
   
3. **Metric Aggregation**: Graphite excels in aggregating and summarizing time-series data efficiently, providing powerful functions for analyzing and manipulating metrics. Grafana, while lacking in native aggregation functions, can integrate with Graphite (or similar databases) to leverage its aggregation capabilities. StatsD, being a lightweight daemon, does not perform aggregation but plays a crucial role in collecting and forwarding metrics data.
   
4. **Alerting and Notifications**: Grafana offers robust alerting features, allowing users to set up alerts based on specified conditions and receive notifications via email, Slack, or other channels. Graphite relies on third-party tools for advanced alerting functionality but can be integrated with alerting systems. StatsD does not include native alerting capabilities, as its primary focus is on data collection and processing.
   
5. **Ease of Use**: Grafana is known for its user-friendly interface and intuitive dashboard creation tools, making it easy for users to visualize and interact with data. Graphite, on the other hand, can be more complex to set up and configure, requiring a deeper understanding of metrics storage and querying. StatsD is simple to deploy and manage, with minimal configuration needed to start collecting metrics.
   
6. **Community Support and Ecosystem**: Grafana has a large and active community that contributes plugins, dashboards, and integrations, enhancing its functionality and compatibility with various data sources. Graphite also has a supportive community but may not offer as many integrations and extensions as Grafana. StatsD benefits from a strong ecosystem of integrations with various services and tools that complement its metric collection capabilities.

In Summary, Grafana is a powerful visualization tool, Graphite excels in storing and analyzing time-series data, while StatsD focuses on collecting and forwarding metrics efficiently in real-time applications. Each tool serves a specific role in the metrics and observability ecosystem, offering unique advantages and capabilities to users.

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Advice on StatsD, Graphite, Grafana

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
StackShare
StackShare

Jun 25, 2019

Needs advice

From a StackShare Community member: “We need better analytics & insights into our Elasticsearch cluster. Grafana, which ships with advanced support for Elasticsearch, looks great but isn’t officially supported/endorsed by Elastic. Kibana, on the other hand, is made and supported by Elastic. I’m wondering what people suggest in this situation."

663k views663k
Comments

Detailed Comparison

StatsD
StatsD
Graphite
Graphite
Grafana
Grafana

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).

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

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.

Network daemon; Runs on the Node.js platform; Sends aggregates to one or more pluggable backend services
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
Create, edit, save & search dashboards;Change column spans and row heights;Drag and drop panels to rearrange;Use InfluxDB or Elasticsearch as dashboard storage;Import & export dashboard (json file);Import dashboard from Graphite;Templating
Statistics
GitHub Stars
-
GitHub Stars
6.0K
GitHub Stars
70.7K
GitHub Forks
-
GitHub Forks
1.3K
GitHub Forks
13.1K
Stacks
373
Stacks
383
Stacks
18.4K
Followers
293
Followers
419
Followers
14.6K
Votes
31
Votes
42
Votes
415
Pros & Cons
Pros
  • 9
    Open source
  • 7
    Single responsibility
  • 5
    Efficient wire format
  • 3
    Loads of integrations
  • 3
    Handles aggregation
Cons
  • 1
    No authentication; cannot be used over Internet
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
  • 89
    Beautiful
  • 68
    Graphs are interactive
  • 57
    Free
  • 56
    Easy
  • 34
    Nicer than the Graphite web interface
Cons
  • 1
    No interactive query builder
Integrations
Node.js
Node.js
Docker
Docker
Sensu
Sensu
Nagios
Nagios
Logstash
Logstash
Windows Server
Windows Server
Netdata
Netdata
Riemann
Riemann
Diamond
Diamond
Telegraf
Telegraf
collectd
collectd
Ganglia
Ganglia
InfluxDB
InfluxDB

What are some alternatives to StatsD, Graphite, Grafana?

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.

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.

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.

Sysdig

Sysdig

Sysdig is open source, system-level exploration: capture system state and activity from a running Linux instance, then save, filter and analyze. Sysdig is scriptable in Lua and includes a command line interface and a powerful interactive UI, csysdig, that runs in your terminal. Think of sysdig as strace + tcpdump + htop + iftop + lsof + awesome sauce. With state of the art container visibility on top.

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