Scaling aggregates with dataflow: A case study in real-time aggregation

Box faced significant challenges in maintaining real-time accuracy for folder size and item counts due to the high volume of file operations, leading to database overload and inefficiencies in their legacy system. To address this, Box transitioned from standard streaming patterns to a custom Dataflow-based solution using a hybrid session-gap approach, which effectively balanced database efficiency and user-visible updates. This new approach incorporated fixed-length session windows and a watermark-based mechanism, enabling more controlled and predictable aggregation while significantly reducing write traffic and infrastructure costs. The optimized pipeline achieved a 67% reduction in database load, saving approximately $300k annually and improving system reliability and user experience, demonstrating that strategic streaming aggregation can enhance both cost efficiency and performance without compromising user satisfaction.

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