Understanding DataTurbine

The Goal

Let’s say you have some data you’re collecting. Could be, say, weather data. Could be load readings from a bridge, pictures from a security camera, GPS-tagged biometrics from a tracked tiger, chlorophyll readings from a lake buoy, or pretty much anything else you can think of. Add in data from another system, and now stir in the requirement of multiple viewers. In other words, you have a system with lots of disparate data that you want to see, share and process.

DataTurbine is an excellent solution. It’s probably even answering needs that you didn’t know you had! Briefly, DataTurbine lets you stream data and see it in real-time. But it also lets you TiVo through old and new data, share it with anyone over the network, do real-time processing of the streams and more.

A Free Open Source Solution

In 2007, DataTurbine was transitioned from commercial to open source under the Apache 2.0 license. All code and documentation are public and available from the project web site. Current DataTurbine related research includes projects sponsored by NSF, NASA, and the Gordon and Betty Moore Foundation.

What DataTurbine Does Best

  • Reliable Data Transfer
  • Real-Time Data
    • Streaming
    • Analysis
    • Visualization
    • Publication
  • Cleanly works with heterogeneous data types
  • Separates data acquisition (sources) from data utilization (sinks)
  • Seamlessly access historical and real time data
  • Synchronized access across disparate data channels

What DataTurbine Is Not Good At

  • Replacing a database (DataTurbine should be used with a database)
  • Out of order data (Data is accepted chronologically)
  • Back-loading data

The Parts

DataTurbine consists of one or more servers accepting data from sources and serving them up to sinks. Each component can be located on the same machine or different machines, allowing for flexibility in the deployment.

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