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Table Of Contents
Engineering Lakehouses with Open Table Formats
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The growing adoption of lakehouse architectures has changed the way organizations store, process, and analyze data. Open table formats such as Apache Hudi, Apache Iceberg, and Delta Lake offer flexibility and avoid vendor lock-in by keeping the data tier open and independent, enabling teams to choose best-in-class tools for their specific needs. Yet, as organizations scale out their operations or onboard newer workloads, they encounter challenges that demand interoperability between these formats and systems.
Practitioners care deeply about this because table format lock-in can introduce costly friction—limiting the ability to switch query engines, complicating cross-team collaboration, and increasing operational overhead due to unnecessary data copying or format migration. Whether it’s a data engineering team relying on Spark with Apache Hudi, or an analytics team using Trino with Apache Iceberg, the ability to operate across formats...