MAKING USER-SEQUENCE DATA MORE COST-EFFICIENT, FASTER, AND EASIER TO USE

Summary from the TLDR Dev newsletter

Pinterest redesigned its machine learning data platform to use a single configuration-as-code definition that standardizes user-sequence data across real-time indexing, batch processing, and online serving. This lambda-style architecture and columnar, time-partitioned storage model reduced infrastructure costs while speeding up the onboarding of new events and enrichments.