Lakehouse or Warehouse? Part 2 of 2
Blog post from Onehouse
In the second part of his talk at Data Council Austin in March 2022, Onehouse CEO Vinoth Chandar delves into the comparison of data warehouses and data lakehouses, focusing on their capabilities and price/performance attributes. He notes that while both architectures support core functionalities like updates and transactions, data warehouses often offer more complete relational database features, whereas lakehouses cater to higher-scale data needs and require hands-on management. Chandar highlights that the choice between warehouses and lakehouses hinges on workload requirements, with warehouses offering managed services and lakehouses providing flexibility but necessitating self-management. He discusses the evolving landscape of query optimization, the importance of benchmarking workloads to determine cost-effectiveness, and the advantages of a lakehouse-first architecture, which supports openness, interoperability, and a unified data source for both BI and data science teams. The talk concludes with best practices for leveraging lakehouses, emphasizing their ability to offer cost-effective ETL solutions while maintaining high performance and adaptability to emerging technologies like ML and streaming.
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