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Hybrid Data

Hybrid Data manages vast amounts of location based content in the cloud, syncing appropriate layers into connected cars and devices whenever an Internet connection is available.

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