LogMeIn has relaunched its cloudy-thing management, now called Xively and available with a sixty-quid ARM development board for those hoping to kick start the Internet of Things.
Not that one needs the £57.99 Jumpstart kit to use Xively's cloud. Support for RESTful, JSON and CSV as well as raw sockets ensure that any IP-capable device can communicate with the Xively cloud to store and process data as the company aspires to become the preferred cloud service for the Internet of Things.
Until Tuesday, Xively was known as Cosm, and prior to that the inexplicably-spelt Pachube (pronounced "Patch Bay") which was set up 2008 to aggregate sensor data.
LogMeIn acquired the company back in 2011, by which time it was already processing seven million data points daily and burning through $4m in annual running costs which LogMeIn took on when it bought the company for $15m. LogMeIn already had its own cloud, monikered Gravity, onto which the Pachube service was grafted.
To recover those costs, Xively will charge a sliding scale kicking off at thousand dollars a year, but not until commercial deployment. Developer and hobbist accounts are free to use, and the deal with ARM creates a Jumpstart kit complete with an mbed Application board and LPC1768 Header board with which to start logging data.
The IoT is coming, and while one might debate if there'll be 50 billion things or 5 billion things, they will still need an equivalent number of database records – so companies are vying to host that data. Google will be showing off its own Cloud Service at its annual developer conference this week, blanketing the site with ZigBee-networked sensors pouring 4,000 data streams into the Google Cloud Platform to show what it can do.
Google is cheaper than Xively, starting at $9 a month, but LogMeIn reckons that having a cloud designed specifically for IoT applications will make it more attractive. One might also guess that companies will be reluctant to share their data with the Googleplex - which is best known for exploiting other peoples' data for its own gain.