Principal, SanjMo & Former Gartner Research VP, Data & Analytics | Author | Podcast Host | Medium Blogger
On the occasion of Onehouse’s $35M Series B funding, I had the pleasure of discussing the intricacies of lakehouse architecture and table formats with founder and CEO, Vinoth Chandar. He created the Hudi format while at Uber and then worked at Confluent, before starting Onehouse. Our conversation delved into the origins and differences between Apache Hudi, Apache Iceberg, and Delta Lake. https://lnkd.in/gZTTaqq3 The complexity behind table formats and metadata is truly remarkable. Vinoth shared insights into achieving interoperability through Databricks UniForm and @Apache XTable, developed in collaboration with Microsoft and Google. We also explored technical aspects of meta stores and catalogs, such as Snowflake’s Polaris and Databricks’ Unity Catalog. Vinoth also offered his perspective on Tabular (now part of Databricks) and the future of lakehouse management. I believe you'll find this episode insightful and valuable. Feel free to share your thoughts and feedback! #data #datamanagement #ai #ml #cloud #multicloud #moderndatastack #cloudnative #opensource #llm #lakehouse #apacheiceberg #apachehudi #LFDelta
It Depends #65: Iceberg, Delta, Hudi, Polaris, Unity & Lakehouse - Vinoth Chandar Onehouse - Jun ’24
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Thanks for sharing Sanjeev Mohan
data engineer who likes to software engineer
2wI enjoyed listening to this conversation. Quite insightful. I found Vinoth's scnenario sketch of Iceberg becoming the standard "plain table format" (like Parquet is the standard "plain file format") and Delta/Hudi further evolving to higher-level abstractions (including compute services) an interesting take.