Customer Challenges

Meet SLA and reduce cost of data processing and storage

  • High volume and velocity of transactions
  • 4 billion transactions per day
  • 6 petabytes growing at 12 terabytes per month
  • High cost of operation on Teradata platform
  • Meeting strict SLA was di_cult


  • Re-engineer S&T application running on Teradata to Hadoop
  • Provide a solution for processing and storing large volume of data within stipulated SLA
  • Generate external vendor reports within SLA


  • Hadoop (HDFS) framework for storing data
  • Business logic implemented in Hive
  • Oozie for orchestrating workflows
  • Load generated reports into Geneva document server


  • Reduced IT hardware costs
  • Reduced development life cycle
  • Scalable and fault tolerant infrastructure
  • Better adherence to SLA


  • 18 types of reports supported - sales, preorder, events
  • 500K+ reports generated daily
  • Massive usage: 5M+ users from 2.5M+ vendors


  • Support for all report types
  • Auto failover between clusters – Near zero downtime DR
  • Users access reports through API

Enterprise app for Media sales