Business Impact

  • Reduction in costs by shifting to server less architecture

  • Reduction in pipeline SLAs as a result of query optimization

  • Enhanced performance, ease of data management and seamless scaling

Customer Key Facts

  • Location : United States
  • Industry : Food & Beverage

Problem Context 

The client is a US-based wholesale food distributor and supplier that provides packaging, demand planning, inbound freight consolidation, delivery route optimization, etc., for manufacturers and retailers.
They sought to scale up their existing in-house data application, which is used by their user base to pull data records on a subscription basis to accommodate a more extensive subscriber base.


  • Assessment required a detailed study of the client’s current application architecture 
  • Revamped necessary application to be scalable to accommodate a more extensive subscriber base

Technologies Used

Amazon RDS
Amazon SQS
Amazon S3
Amazon Lambda
Amazon Athena

Solution Approach and Overview

Quantiphi performed a deep-dive assessment of the client’s existing application architecture, identified the key issues and gaps, provided performance optimization recommendations, and assisted in implementing the proposed changes.

Solution Key Features

  • Provided recommendations on utilization and optimization of Athena queries, migration to Aurora serverless, and existing table restructuring
  • Quantiphi’s Project team performed a 13.07% overall optimization of 12 Athena queries to reduce pipeline SLAs
  • Restructured the table to avoid deadlocks due to multiple lambda functions running in parallel


Successfully enabled workload migration and optimization of the client’s pipeline to yield a more scalable application

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