DataTurbine

In a Nutshell

DataTurbine is a robust real-time streaming data engine that lets you quickly stream live data from experiments, labs, web cams and even Java enabled cell phones. It acts as a "black box" to which applications and devices send and receive data. Think of it as express delivery for your data, be it numbers, video, sound or text.

DataTurbine is a buffered middleware, not simply a publish/subscribe system. It can receive data from various sources (experiments, web cams, etc) and send data to various sinks (visualization interfaces, analysis tools, databases, etc). It has "TiVO" like functionality that lets applications pause and rewind live streaming data.

DataTurbine is open source and free. There is also an active developer and user community that continues to evolve the software and assist in application development.

Why Use It?

  • Extendable: It is a free Open Source project with an extensive well documented API.
  • Scalable: It uses a hierarchical design that allows a network structure that grows with the requirements of your application
  • Portable: DataTurbine runs on devices ranging from phones & buoys to multicore servers.
  • Dependable: Using a Ring Buffered Network Bus, it provides tunable persistent storage at key network nodes to facilitate reliable data transport
  • Growing: There is also an active developer and user community that continues to evolve the software and assist in application development.

Latest News

Jul 2 2014

OSDT Android SensorPod brochure available now!

A new tri-fold brochure describing the OSDT SensorPod is now available.  It contains a short description of the SensorPod, what it can do, and its benefits.  It also illustrates three SensorPod case studies: 1) a lake deployment in the North Temperate Lake LTER Network site, Wisconsin, 2) a terrestrial forest deployment at the Taiwan Forestry Research Institute (TFRI), and 3) a pier deployment for ocean acidification research at Scripps Institution of Oceanography, UCSD.  As the brochure explains, we developed the SensorPod Kit to enable research groups to deploy inexpensi