[{"data":1,"prerenderedAt":78},["ShallowReactive",2],{"term-l\u002Flakehouse":3,"related-l\u002Flakehouse":60},{"id":4,"title":5,"acronym":6,"body":7,"category":40,"description":41,"difficulty":42,"extension":43,"letter":44,"meta":45,"navigation":46,"path":47,"related":48,"seo":54,"sitemap":55,"stem":58,"subcategory":6,"__hash__":59},"terms\u002Fterms\u002Fl\u002Flakehouse.md","Lakehouse",null,{"type":8,"value":9,"toc":33},"minimark",[10,15,19,23,26,30],[11,12,14],"h2",{"id":13},"eli5-the-vibe-check","ELI5 - The Vibe Check",[16,17,18],"p",{},"For years you had to pick a side: a data warehouse, structured, fast, expensive, or a data lake, cheap, flexible, and a mess nobody fully trusted. A lakehouse is the peace treaty, cheap object storage doing the warehouse's job by adding an open table format like Iceberg or Delta Lake on top, so you get warehouse-grade reliability without giving up lake-grade cheapness and flexibility.",[11,20,22],{"id":21},"real-talk","Real Talk",[16,24,25],{},"A lakehouse is an architecture that combines the low-cost, flexible storage of a data lake with the ACID transactions, schema enforcement, and performance optimizations traditionally found in a data warehouse. It is typically implemented using an open table format (Iceberg, Delta Lake, or Hudi) over files in object storage, queried by multiple engines instead of one proprietary warehouse.",[11,27,29],{"id":28},"when-youll-hear-this","When You'll Hear This",[16,31,32],{},"\"We're moving off the warehouse to a lakehouse so any engine can query the same data.\" \u002F \"Databricks and Snowflake are both racing to own the lakehouse story.\"",{"title":34,"searchDepth":35,"depth":35,"links":36},"",2,[37,38,39],{"id":13,"depth":35,"text":14},{"id":21,"depth":35,"text":22},{"id":28,"depth":35,"text":29},"architecture","For years you had to pick a side: a data warehouse, structured, fast, expensive, or a data lake, cheap, flexible, and a mess nobody fully trusted.","intermediate","md","l",{},true,"\u002Fterms\u002Fl\u002Flakehouse",[49,50,51,52,53],"Apache Iceberg","Delta Lake","Data Warehouse","Data Lake","Data Mesh",{"title":5,"description":41},{"changefreq":56,"priority":57},"weekly",0.7,"terms\u002Fl\u002Flakehouse","vSKnchHlaDkoQ8nqpXz4FOzpkiv_RWTkTDmtzch5Qvw",[61,66,69,72,75],{"title":49,"path":62,"acronym":6,"category":63,"difficulty":64,"description":65},"\u002Fterms\u002Fa\u002Fapache-iceberg","database","advanced","Imagine a giant folder of Parquet files that used to be pure chaos, nobody knew which files were current, nobody could add a column safely, and two people...",{"title":52,"path":67,"acronym":6,"category":63,"difficulty":42,"description":68},"\u002Fterms\u002Fd\u002Fdata-lake","A data lake is a massive storage dump where you throw every piece of data in its raw format. CSV files, JSON, images, logs, whatever.",{"title":53,"path":70,"acronym":6,"category":40,"difficulty":64,"description":71},"\u002Fterms\u002Fd\u002Fdata-mesh","Instead of one giant warehouse where ALL the company's data goes (and one poor team manages it), Data Mesh says 'each team owns their own data like it's a ",{"title":51,"path":73,"acronym":6,"category":63,"difficulty":42,"description":74},"\u002Fterms\u002Fd\u002Fdata-warehouse","A data warehouse is where all your company's data goes to be analyzed.",{"title":50,"path":76,"acronym":6,"category":63,"difficulty":64,"description":77},"\u002Fterms\u002Fd\u002Fdelta-lake","Delta Lake is Iceberg's cousin from the Databricks side of the family, same basic idea: bolt ACID transactions and version history onto a pile of Parquet f...",1792528095645]