Uber Re-architects Data Lake Ingestion Platform
Uber engineers re-architected the company's data lake ingestion platform, replacing scheduled Spark batch jobs with a streaming-first system named IngestionNext. The new pipeline uses Kafka, Flink, and Apache Hudi to reduce ingestion latency from hours to minutes, support thousands of datasets, and cut compute usage by roughly 25%. A control plane, compaction strategies, and failover mechanisms maintain correctness and availability.
Scoring Rationale
Strong enterprise engineering with measurable latency and cost benefits; limited novelty beyond established streaming-first patterns.
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