Maritz Global Events eventBit – Faster Data Capture and Processing with AWS

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Thorn Technologies helps Maritz Global Events leverage Amazon Web Services to collect and process massive amounts of event attendee location data faster.

The Problem

Maritz Global Events, one of the largest and most innovative event management companies, builds a software platform called eventBit that collects event attendee location data via beacons and processes it. Event organizers and sponsors can then use this data to glean insights about the location and movements of attendees throughout the event. Maritz Global Events was preparing for one of the largest trade shows in the world, where they expected to collect 15 times more data than any previous event the company helped manage. Thus, Maritz Global Events needed to build a robust solution that could capture and process billions of data points quickly, which would help them provide their clients with more powerful reporting capabilities.

The Solution

Maritz Global Events engaged Thorn Technologies to help build this data capture and processing solution, and the AWS cloud played an integral role. Thorn Technologies helped set up the back-end architecture of the solution as such:
  • API Gateway and Lambda were integrated to create a cloud-native serverless API that initiates the capture of the beacon data.
  • Then Kinesis Firehose delivers the beacon data to Redshift, which replaced MongoDB, for processing.
  • Finally, Data Pipeline exports the data to another Redshift instance for reporting purposes.

The Results

The new cloud architecture significantly increased the speed of data capture and processing for Maritz Global Event’s software. The system can now process at least 240,000 captures per second (approximately 3 times faster than prior solutions) in real time on a 6-node cluster that costs only $1.50/hr. Furthermore, the solution has the ability to scale on demand to support multiple billions of data captures for events of any size. Maritz Global Events solution now captures and processes data faster and can scale immediately when needed.  

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