{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Data Science Tech Brief By HackerNoon","title":"The Architectural Limits of Data Lakes and the Rise of Lakehouses","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/eef5ef9a\"></iframe>","width":"100%","height":180,"duration":543,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/the-architectural-limits-of-data-lakes-and-the-rise-of-lakehouses.\n             Data lakes solve storage but not reliability. Learn how lakehouse architecture adds transactions, metadata, and governance to fix the gap. \n            Check more stories related to data-science at: https://hackernoon.com/c/data-science.\n            You can also check exclusive content about #data-governance, #data-lakehouse, #delta-lake, #acid-transactions, #schema-evolution, #open-table-formats, #apache-hudi, #data-architecture,  and more.\n            \n            \n            This story was written by: @seshendranath. Learn more about this writer by checking @seshendranath's about page,\n            and for more stories, please visit hackernoon.com.\n            \n                \n                \n                Raw files on object storage are great for cheap retention but terrible as a system of record lakehouse architecture adds transactional tables, versioned metadata, and schema contracts on top of the same storage, turning a dumping ground into a reliable analytical platform.\n        \n        ","thumbnail_url":"https://img.transistorcdn.com/8VxAgS1Ll3FJEERcAdhFdqqXJMnE7OfD2RUvrjauLt0/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMjY4LzE2ODM1/ODI1ODUtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}