Hybrid Data Overview

Hybrid Data addresses some common problems including:

  • Aggregating and managing location based content from many different providers
  • Making location based content available from cars, PNDs and other intermittently connected devices
  • Future-proofing services against changes in content providers

Hybrid Data uses an intelligent sync algorithm to predict what data is needed by a car or device based on the device user’s profile.  Only the content layers and geographic areas that match a user’s profile are synced to the car or device.

Key Features

Key features of Hybrid Data include:

  • Intelligent sync from cloud to device that is respectful of network bandwidth and on-device storage
  • Management of any point, line or polygon data
  • Rapid import of many different content types
  • Complete abstraction from provider-specific taxonomy
  • SDKs for Linux, Android, QNX, WinCE, Windows Phone, iOS, Mac OSX

Import Any Location Content

Data import capabilities include:

  • Map providers like HERE, TomTom, AND, OpenStreetMap
  • Local data providers like Yelp, Foursquare, InfoUSA, Localeze
  • Social networks like Facebook, Twitter
  • Traffic data suppliers like INRIX, HERE
  • Gas price suppliers like OPIS, Gas Buddy
  • Weather providers like The Weather Channel, Weather Decision Technologies