Statsd VS Telegraf

Compare Statsd vs Telegraf and see what are their differences.

Telegraf

Agent for collecting, processing, aggregating, and writing metrics, logs, and other arbitrary data. (by influxdata)
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Statsd Telegraf
6 111
17,488 13,786
0.3% 0.6%
5.1 9.9
4 months ago 1 day ago
JavaScript Go
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Statsd

Posts with mentions or reviews of Statsd. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-04.

Telegraf

Posts with mentions or reviews of Telegraf. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-27.

What are some alternatives?

When comparing Statsd and Telegraf you can also consider the following projects:

Collectd - The system statistics collection daemon. Please send Pull Requests here!

prometheus - The Prometheus monitoring system and time series database.

VictoriaMetrics - VictoriaMetrics: fast, cost-effective monitoring solution and time series database

InfluxDB - Scalable datastore for metrics, events, and real-time analytics

Graphite - A highly scalable real-time graphing system

pfSense-Dashboard - A functional and useful dashboard for pfSense that utilizes influxdb, grafana and telegraf

tcollector - Data collection framework for OpenTSDB

OPNsense-Dashboard - A functional and useful dashboard for OPNsense that utilizes InfluxDB, Grafana, Graylog, and Telegraf.

Diamond - Diamond is a python daemon that collects system metrics and publishes them to Graphite (and others). It is capable of collecting cpu, memory, network, i/o, load and disk metrics. Additionally, it features an API for implementing custom collectors for gathering metrics from almost any source.