USDB: Optimized Storage Architecture for Scalable Recommender Systems at ByteDance

USDB addresses storage challenges in recommender systems by introducing optimized techniques like time-based compaction, differentiated replicas, and hybrid columnar formats, achieving significant reductions in write latency and infrastructure costs. The system enables efficient handling of long user histories through shared sequence maintenance and enhanced read performance across various workloads.

Comments

Read original article