Dremio Lakehouse Analytics with Hudi and Iceberg using XTable
Blog post from Onehouse
Data lakehouse architectures utilizing open table formats like Apache Hudi, Apache Iceberg, and Delta Lake are gaining traction for their flexibility and ability to integrate with various compute engines, allowing organizations to avoid vendor lock-in and adapt to different workloads. A common challenge with these formats is the lack of interoperability, which complicates data unification when different formats are used by different teams within an organization. Apache XTable addresses this challenge by providing a translation layer that allows for seamless metadata conversion between different table formats, such as converting Hudi to Iceberg, without duplicating or altering the underlying data. This capability was demonstrated in a scenario involving two analytics teams: Team A using Apache Hudi with Spark and Team B using Dremio with Iceberg. Apache XTable enabled Team B to access and analyze Team A's Hudi data as if it were in Iceberg format, facilitating a unified analysis of sales data from two different superstores. This interoperability streamlines analytical processes, reduces costs associated with data migration, and maintains the integrity of historical data, highlighting the practical benefits of XTable in overcoming format barriers in data analytics.
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