How to design partition keys, sort keys and a serving layer when your data has two sources with different SLAs Batch pipelines are reliable, auditable, and built to handle complexity at scale, but they come with a cost: by the time data is consolidated, validated, and ready to serve, hours or days might have passed. For internal analytics that’s often fine, but for a customer staring at a mobile app wondering whether their action was registered, it is not. This article is about a DynamoDB modeling problem that lives at that boundary. The case study below is fictional and designed to keep the focus on the technical problem rather than on any specific domain. Business rules and delays are simplified accordingly. The core challenge is one that appears frequently in data-intensive systems: a batch pipeline owns the authoritative view of the data, but its consolidation cycle introduces a lag that makes the user-facing experience feel stale.…