RRDTool

RRDTool

RRDTool is open source software for logging and graphing time-series data. It is useful for monitoring server and network statistics over time.
RRDTool image
timeseries logging graphing monitoring server network statistics

RRDTool: Open Source Time Series Data Logging and Graphing Software

Monitor server and network statistics over time with RRDTool, a free and open-source tool for logging and graphing time-series data.

What is RRDTool?

RRDTool (Round Robin Database Tool) is an open source data logging and graphing system for time series data. It allows you to store numeric data over time and then visualize that data through graphs and charts.

Some key features of RRDTool include:

  • Efficient storage of time-series data through round-robin databases
  • Automated data consolidation for long-term storage
  • Customizable data aggregation for averages, min/max, sums, etc.
  • Graphing and visualization functionality
  • Support for RRD files for portable data storage
  • Command line and API access for scripting and integration

RRDTool is commonly used for monitoring server performance and network traffic over time. Typical applications include tracking CPU load, memory usage, network bandwidth, disk IO, application response times, and many other statistics. The data consolidation features make it efficient for long-term data storage and the graphing makes it easy to spot trends.

RRDTool was created by Tobi Oetiker and is released under the open source GNU General Public License. It runs on Linux, Windows, and other platforms and can store data from many sources including log files, monitoring tools, applications, and custom scripts.

RRDTool Features

Features

  1. Data logging and graphing
  2. Round Robin Database for efficient storage
  3. Built-in consolidation functions
  4. Customizable graphs and web interface
  5. Rule-based alarming
  6. Pluggable back-end database

Pricing

  • Open Source

Pros

Lightweight and efficient

Flexible and customizable

Open source and free

Wide range of graphing and analysis options

Handles large datasets well

Cons

Steep learning curve

Configuration can be complex

Limited native support for very large datasets

RRD files difficult to transport or migrate


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