Apache Hudi
Apache Hudi (Hadoop Upserts Deletes and Incrementals) is an open-source data management framework that enables incremental data processing on data lakes. It provides transactional capabilities, upserts, deletes, and change data capture on top of cloud storage or Hadoop Distributed File System (HDFS), making data lakes more efficient and reliable for real-time analytics. Hudi integrates with popular big data processing engines like Apache Spark, Apache Flink, and Presto to handle large-scale data workloads.
Developers should learn Apache Hudi when building or managing data lakes that require real-time data ingestion, efficient upserts/deletes, and incremental processing for analytics. It is particularly useful in scenarios like streaming ETL pipelines, real-time dashboards, and compliance-driven data management where data freshness and transactional consistency are critical. Hudi helps reduce data latency and storage costs by avoiding full table scans and enabling incremental queries.