Apache Iceberg™ vs Delta Lake vs Apache Hudi™ - Feature Comparison Deep Dive
Blog post from Onehouse
As the data lakehouse architecture gains popularity, a significant focus has emerged on comparing three core open-source projects: Apache Hudi, Delta Lake, and Apache Iceberg, with an updated analysis considering their latest features as of October 2025. These projects, often viewed as mere table formats, are increasingly recognized for their capabilities in managing modern data workloads involving continuous updates. While Delta Lake and Iceberg are optimized for append-only tasks, Apache Hudi excels in supporting mutable workloads with its innovative features such as Merge On Read, incremental pipelines, and multi-modal indexing, making it a favored choice for complex data processing needs. The introduction of Apache XTable promises interoperability across these formats, eliminating the need to choose a single one. The comparison also highlights Hudi's advanced concurrency control and its robust community engagement, alongside performance benchmarks that place Delta and Hudi on par, while Iceberg lags behind. The text underscores the importance of evaluating these technologies based on specific use cases rather than solely relying on feature checklists or benchmarks, and suggests that Apache Hudi, with its pioneering features and strong community support, stands out for handling mature workloads.
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