Cacti vs StatsD

Overview

StatsD

Stacks373

Followers293

Votes31

Cacti

Stacks89

Followers202

Votes10

Cacti vs StatsD: What are the differences?

Introduction

Cacti and StatsD are both monitoring tools that help track various metrics and performance data. However, there are some key differences between the two that should be noted.

Data Collection Method: Cacti is a graphing solution that collects data through SNMP (Simple Network Management Protocol), while StatsD is a network daemon that collects statistics and performance metrics using UDP (User Datagram Protocol) packets. This difference in data collection methods can impact the efficiency and real-time nature of the data being collected.
Graphing Capabilities: Cacti provides a robust graphing feature that allows users to create detailed visual representations of their data using RRDtool. On the other hand, StatsD focuses more on collecting and aggregating raw metrics without providing built-in graphing capabilities. Users often need to integrate StatsD with other tools like Grafana for visualization.
Alerting and Notification: Cacti has built-in alerting functionalities that allow users to set thresholds and receive notifications when metrics exceed defined limits. In contrast, StatsD lacks native alerting capabilities and requires integration with other monitoring tools for setting up alerts and notifications.
Storage Backend: Cacti stores its metrics data in RRD (Round-Robin Database) files by default, which are optimized for time-series data. StatsD, on the other hand, does not come with a built-in storage backend and typically relies on other databases like Graphite or InfluxDB for data persistence.
Ecosystem and Plugins: Cacti has a well-established community and a wide range of plugins available for extending its functionalities. On the contrary, StatsD has a smaller ecosystem and may require more customization or integration with other tools to meet specific monitoring requirements.

In Summary,

Cacti and StatsD differ in their data collection methods, graphing capabilities, alerting features, storage backends, and ecosystem support.

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CLI (Node.js)

Manual

Detailed Comparison

StatsD	Cacti
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).	Cacti is a complete network graphing solution designed to harness the power of RRDTool's data storage and graphing functionality. Cacti provides a fast poller, advanced graph templating, multiple data acquisition methods, and user management features out of the box.
Network daemon; Runs on the Node.js platform; Sends aggregates to one or more pluggable backend services	Unlimited number of graph items can be defined for each graph optionally utilizing CDEFs or data sources from within cacti.;Automatic grouping of GPRINT graph items to AREA, STACK, and LINE[1-3] to allow for quick re-sequencing of graph items.;Auto-Padding support to make sure graph legend text lines up.;Graph data can be manipulated using the CDEF math functions built into RRDTool. These CDEF functions can be defined in cacti and can be used globally on each graph.;Data sources can be created that utilize RRDTool's "create" and "update" functions. Each data source can be used to gather local or remote data and placed on a graph.
Statistics
Stacks 373	Stacks 89
Followers 293	Followers 202
Votes 31	Votes 10
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 3 Rrdtool based 3 Free 2 Fast poller 1 Graphs from snmp 1 Graphs from language independent scripts
Integrations
Node.js Docker Graphite	RRDtool

What are some alternatives to StatsD, Cacti?

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 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 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 is a host/service/network monitoring program written in C and released under the GNU General Public License.

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 is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

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

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, a Distributed Tracing System

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Cacti vs StatsD: What are the differences?

Introduction

Cacti and StatsD are both monitoring tools that help track various metrics and performance data. However, there are some key differences between the two that should be noted.

Data Collection Method: Cacti is a graphing solution that collects data through SNMP (Simple Network Management Protocol), while StatsD is a network daemon that collects statistics and performance metrics using UDP (User Datagram Protocol) packets. This difference in data collection methods can impact the efficiency and real-time nature of the data being collected.
Graphing Capabilities: Cacti provides a robust graphing feature that allows users to create detailed visual representations of their data using RRDtool. On the other hand, StatsD focuses more on collecting and aggregating raw metrics without providing built-in graphing capabilities. Users often need to integrate StatsD with other tools like Grafana for visualization.
Alerting and Notification: Cacti has built-in alerting functionalities that allow users to set thresholds and receive notifications when metrics exceed defined limits. In contrast, StatsD lacks native alerting capabilities and requires integration with other monitoring tools for setting up alerts and notifications.
Storage Backend: Cacti stores its metrics data in RRD (Round-Robin Database) files by default, which are optimized for time-series data. StatsD, on the other hand, does not come with a built-in storage backend and typically relies on other databases like Graphite or InfluxDB for data persistence.
Ecosystem and Plugins: Cacti has a well-established community and a wide range of plugins available for extending its functionalities. On the contrary, StatsD has a smaller ecosystem and may require more customization or integration with other tools to meet specific monitoring requirements.

In Summary,

Cacti and StatsD differ in their data collection methods, graphing capabilities, alerting features, storage backends, and ecosystem support.