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collectd vs StatsD: What are the differences?
collectd: System and applications metrics collector. 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; StatsD: Simple daemon for easy stats aggregation. StatsD is a front-end proxy for the Graphite/Carbon metrics server, originally written by Etsy's Erik Kastner. StatsD is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP and sends aggregates to one or more pluggable backend services (e.g., Graphite).
collectd and StatsD can be categorized as "Monitoring" tools.
Some of the features offered by collectd are:
- fast
- simple
- integrated
On the other hand, StatsD provides the following key features:
- buckets: Each stat is in its own "bucket". They are not predefined anywhere. Buckets can be named anything that will translate to Graphite (periods make folders, etc)
- values: Each stat will have a value. How it is interpreted depends on modifiers. In general values should be integer.
- flush: After the flush interval timeout (defined by config.flushInterval, default 10 seconds), stats are aggregated and sent to an upstream backend service.
collectd and StatsD are both open source tools. It seems that StatsD with 14.2K GitHub stars and 1.83K forks on GitHub has more adoption than collectd with 2.26K GitHub stars and 1.08K GitHub forks.
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.
Pros of collectd
- Open Source2
- Modular, plugins2
- KISS1
Pros of StatsD
- Open source9
- Single responsibility7
- Efficient wire format5
- Loads of integrations3
- Handles aggregation3
- Many implementations1
- Scales well1
- Simple to use1
- NodeJS1
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Cons of collectd
Cons of StatsD
- No authentication; cannot be used over Internet1