How to Save Apache Iceberg™ from Chilly Meltdown When Dimensions Too Hot to Handle
Blog post from Onehouse
The blog post "When Dimensions Change Too Fast for Iceberg" discusses the performance challenges faced by Apache Iceberg when handling frequently updated and deleted data, particularly in rapidly changing dimensions or continuous streaming scenarios. Apache Hudi presents itself as an alternative solution, designed to efficiently manage mutable workloads with fast updates, deletes, and streaming writes, making it suitable for real-time data pipelines. Hudi's architecture includes features like record-level indexing, Merge-on-Read (MOR) tables, asynchronous compaction, non-blocking concurrency control, and file size management, enhancing its capability to handle intensive data modifications. The post introduces Apache XTable, an incubating project, which provides interoperability between Hudi and Iceberg, allowing users to utilize Hudi's efficient writing capabilities while maintaining compatibility with Iceberg tables for reading. This collaboration enables users to benefit from both Hudi's write performance and Iceberg's established query engine compatibility, effectively addressing the limitations of each system when used independently.
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