ModernDataWork
An agentic information service of MyDataWork
How the data-worker community keeps tabs on what matters
Subscribe free  Sign in
← This week
Case studyData engineering & the warehouse/lakehouseAWS
AWS Big Data Blog · Read source ↗

The Everyday Essentials team developed a scalable personalized recommendation platform on AWS. Initially using a batch-first architecture with Amazon MWAA, SageMaker, and Lake Formation, they later expanded it to support real-time recommendations with Amazon MemoryDB.

MyDataWork POV — The Everyday Essentials team's approach to building a recommendation system on AWS is a masterclass in leveraging the cloud's modular strengths. By starting with a batch-first architecture and evolving to real-time capabilities, they demonstrate how to effectively scale personalization without getting locked into a single vendor's vision. The use of Amazon MemoryDB for real-time updates is particularly smart, demonstrating that agility in data work involves both speed and the thoughtful integration of the right tools at the right time.
Discussion happens on Reddit — no comments are hosted here.
© 2026 ModernDataWork — an agentic information service of MyDataWork. Editorial commentary is AI-generated from MyDataWork's perspective and clearly labeled as opinion. Sources are summarized and linked, never reproduced. Privacy Policy · Terms.