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RRDtool
RRDtool

4
9
+ 1
3
StatsD
StatsD

192
126
+ 1
27
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RRDtool vs StatsD: What are the differences?

Developers describe RRDtool as "High performance data logging and graphing system for time series data". RRDtool lets you log and analyze the data you gather from all kinds of data-sources (DS). The data analysis part of RRDtool is based on the ability to quickly generate graphical representations of the data values collected over a definable time period. On the other hand, StatsD is detailed as "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).

RRDtool and StatsD can be primarily classified as "Monitoring" tools.

"Do one thing and do it well" is the top reason why over 2 developers like RRDtool, while over 6 developers mention "Single responsibility" as the leading cause for choosing StatsD.

RRDtool and StatsD are both open source tools. StatsD with 14.2K GitHub stars and 1.83K forks on GitHub appears to be more popular than RRDtool with 571 GitHub stars and 199 GitHub forks.

What is RRDtool?

RRDtool lets you log and analyze the data you gather from all kinds of data-sources (DS). The data analysis part of RRDtool is based on the ability to quickly generate graphical representations of the data values collected over a definable time period.

What is StatsD?

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).
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      What are some alternatives to RRDtool and StatsD?
      InfluxDB
      InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.
      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.
      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.
      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.
      See all alternatives
      Decisions about RRDtool and StatsD
      StackShare Editors
      StackShare Editors
      Flask
      Flask
      AWS EC2
      AWS EC2
      Celery
      Celery
      Datadog
      Datadog
      PagerDuty
      PagerDuty
      Airflow
      Airflow
      StatsD
      StatsD
      Grafana
      Grafana

      Data science and engineering teams at Lyft maintain several big data pipelines that serve as the foundation for various types of analysis throughout the business.

      Apache Airflow sits at the center of this big data infrastructure, allowing users to “programmatically author, schedule, and monitor data pipelines.” Airflow is an open source tool, and “Lyft is the very first Airflow adopter in production since the project was open sourced around three years ago.”

      There are several key components of the architecture. A web UI allows users to view the status of their queries, along with an audit trail of any modifications the query. A metadata database stores things like job status and task instance status. A multi-process scheduler handles job requests, and triggers the executor to execute those tasks.

      Airflow supports several executors, though Lyft uses CeleryExecutor to scale task execution in production. Airflow is deployed to three Amazon Auto Scaling Groups, with each associated with a celery queue.

      Audit logs supplied to the web UI are powered by the existing Airflow audit logs as well as Flask signal.

      Datadog, Statsd, Grafana, and PagerDuty are all used to monitor the Airflow system.

      See more
      Łukasz Korecki
      Łukasz Korecki
      CTO & Co-founder at EnjoyHQ · | 6 upvotes · 57.3K views
      atEnjoyHQEnjoyHQ
      Stackdriver
      Stackdriver
      Clojure
      Clojure
      StatsD
      StatsD
      Google Compute Engine
      Google Compute Engine
      collectd
      collectd

      We use collectd because of it's low footprint and great capabilities. We use it to monitor our Google Compute Engine machines. More interestingly we setup collectd as StatsD replacement - all our Clojure services push application-level metrics using our own metrics library and collectd pushes them to Stackdriver

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      Amazon CloudWatch
      Amazon CloudWatch
      PagerDuty
      PagerDuty
      Grafana
      Grafana
      Graphite
      Graphite
      StatsD
      StatsD
      Sentry
      Sentry

      A huge part of our continuous deployment practices is to have granular alerting and monitoring across the platform. To do this, we run Sentry on-premise, inside our VPCs, for our event alerting, and we run an awesome observability and monitoring system consisting of StatsD, Graphite and Grafana. We have dashboards using this system to monitor our core subsystems so that we can know the health of any given subsystem at any moment. This system ties into our PagerDuty rotation, as well as alerts from some of our Amazon CloudWatch alarms (we’re looking to migrate all of these to our internal monitoring system soon).

      See more
      Interest over time
      Reviews of RRDtool and StatsD
      No reviews found
      How developers use RRDtool and StatsD
      Avatar of Stream
      Stream uses StatsDStatsD

      StatsD is used to track the number of messages we're publishing and the type of realtime subscribers. So it shows the number of longpoll connections, the number of websocket connections etc. It also tracks how Redis is performing.

      Avatar of Chris Hartwig
      Chris Hartwig uses StatsDStatsD

      Business and system counters go through StatsD and are pushed to InfluxDB

      Avatar of Tongliang Liu
      Tongliang Liu uses StatsDStatsD

      Arm yourself with sensor all over your application

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