[{"data":1,"prerenderedAt":115},["ShallowReactive",2],{"term-d\u002Fdelta-lake":3,"related-d\u002Fdelta-lake":97},{"id":4,"title":5,"acronym":6,"body":7,"category":77,"description":78,"difficulty":79,"extension":80,"letter":81,"meta":82,"navigation":83,"path":84,"related":85,"seo":91,"sitemap":92,"stem":95,"subcategory":6,"__hash__":96},"terms\u002Fterms\u002Fd\u002Fdelta-lake.md","Delta Lake",null,{"type":8,"value":9,"toc":71},"minimark",[10,15,19,23,26,30,60,64,67],[11,12,14],"h2",{"id":13},"eli5-the-vibe-check","ELI5 - The Vibe Check",[16,17,18],"p",{},"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 files sitting in cloud storage. The trick is a transaction log next to your data that records every single change, so readers always see a consistent table even while writers are mid-write.",[11,20,22],{"id":21},"real-talk","Real Talk",[16,24,25],{},"Delta Lake is an open-source storage layer that brings ACID transactions, scalable metadata handling, and unified batch and streaming processing to data lakes built on Parquet files. It uses a write-ahead transaction log (the _delta_log) to track every commit, enabling time travel, schema enforcement, and safe concurrent writes.",[11,27,29],{"id":28},"show-me-the-code","Show Me The Code",[31,32,37],"pre",{"className":33,"code":34,"language":35,"meta":36,"style":36},"language-sql shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","SELECT * FROM orders VERSION AS OF 12;\n-- or by timestamp:\nSELECT * FROM orders TIMESTAMP AS OF '2026-08-01';\n","sql","",[38,39,40,48,54],"code",{"__ignoreMap":36},[41,42,45],"span",{"class":43,"line":44},"line",1,[41,46,47],{},"SELECT * FROM orders VERSION AS OF 12;\n",[41,49,51],{"class":43,"line":50},2,[41,52,53],{},"-- or by timestamp:\n",[41,55,57],{"class":43,"line":56},3,[41,58,59],{},"SELECT * FROM orders TIMESTAMP AS OF '2026-08-01';\n",[11,61,63],{"id":62},"when-youll-hear-this","When You'll Hear This",[16,65,66],{},"\"Our Spark pipeline writes to Delta Lake so late-arriving records don't corrupt the table.\" \u002F \"Roll back to yesterday's Delta version, the ETL job wrote garbage.\"",[68,69,70],"style",{},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"title":36,"searchDepth":50,"depth":50,"links":72},[73,74,75,76],{"id":13,"depth":50,"text":14},{"id":21,"depth":50,"text":22},{"id":28,"depth":50,"text":29},{"id":62,"depth":50,"text":63},"database","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...","advanced","md","d",{},true,"\u002Fterms\u002Fd\u002Fdelta-lake",[86,87,88,89,90],"Apache Iceberg","Lakehouse","Apache Parquet","Transaction","Data Lake",{"title":5,"description":78},{"changefreq":93,"priority":94},"weekly",0.7,"terms\u002Fd\u002Fdelta-lake","cTPNPIP0QKCFvuHSgtkmef69QSbpl66c7qqI0E6EeQM",[98,101,105,108,112],{"title":86,"path":99,"acronym":6,"category":77,"difficulty":79,"description":100},"\u002Fterms\u002Fa\u002Fapache-iceberg","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":88,"path":102,"acronym":6,"category":77,"difficulty":103,"description":104},"\u002Fterms\u002Fa\u002Fapache-parquet","intermediate","Parquet is a file format that stores your data by column instead of by row, which sounds boring until you realize most analytics queries only touch a handf...",{"title":90,"path":106,"acronym":6,"category":77,"difficulty":103,"description":107},"\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":87,"path":109,"acronym":6,"category":110,"difficulty":103,"description":111},"\u002Fterms\u002Fl\u002Flakehouse","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.",{"title":89,"path":113,"acronym":6,"category":77,"difficulty":103,"description":114},"\u002Fterms\u002Ft\u002Ftransaction","A transaction groups multiple database operations into one all-or-nothing bundle. Either ALL of them succeed, or NONE of them happen.",1792528078262]