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The Journey to the Universal Data Lakehouse

Learn about the paths Apna, Notion, Uber, Walmart, and Zoom took to the Universal Data Lakehouse

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Apna, Notion, Uber, Walmart, Zoom. What do these companies have in common? Aside from their businesses generating massive volumes of data - at high velocity - all of their teams have chosen the universal data lakehouse as a core component of their data stack and pipelines.

Across industries, the universal data lakehouse architecture is delivering significant cost savings, while accelerating data ingestion pipelines and opening up data to a variety of downstream data warehouses, query engines, and data science platforms.

Download this new eBook to learn how, with the Universal Data Lakehouse:

  • Apna improved their data freshness from several hours to just a few minutes
  • Notion saved more than one million dollars in annual infrastructure costs
  • Uber cut pipeline run times by 50%, while reducing ETL costs for critical tables by up to 80%
  • Walmart manages a massive data estate, with data growing at tens of petabytes per day, efficiently
  • Zoom cut their data storage expenses by 90%
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