← This weekCase studyData engineering & the warehouse/lakehouseAWSThe 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.
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