[{"data":1,"prerenderedAt":109},["ShallowReactive",2],{"term-a\u002Fapache-iceberg":3,"related-a\u002Fapache-iceberg":91},{"id":4,"title":5,"acronym":6,"body":7,"category":71,"description":72,"difficulty":73,"extension":74,"letter":75,"meta":76,"navigation":77,"path":78,"related":79,"seo":85,"sitemap":86,"stem":89,"subcategory":6,"__hash__":90},"terms\u002Fterms\u002Fa\u002Fapache-iceberg.md","Apache Iceberg",null,{"type":8,"value":9,"toc":65},"minimark",[10,15,19,23,26,30,54,58,61],[11,12,14],"h2",{"id":13},"eli5-the-vibe-check","ELI5 - The Vibe Check",[16,17,18],"p",{},"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 writing at once could corrupt everything. Iceberg is the librarian who shows up and adds a proper table of contents, version history, and safe locks, all sitting on top of files you already have in cheap object storage.",[11,20,22],{"id":21},"real-talk","Real Talk",[16,24,25],{},"Apache Iceberg is an open table format that adds ACID transactions, schema evolution, hidden partitioning, and time travel on top of data files (typically Parquet) stored in object storage like S3. It gives engines like Spark, Trino, Snowflake, and Flink a shared, versioned view of the same tables without locking you into one compute engine.",[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 FOR VERSION AS OF 1234567890;\n-- Iceberg time travel: query the table exactly as it looked at a past snapshot\n","sql","",[38,39,40,48],"code",{"__ignoreMap":36},[41,42,45],"span",{"class":43,"line":44},"line",1,[41,46,47],{},"SELECT * FROM orders FOR VERSION AS OF 1234567890;\n",[41,49,51],{"class":43,"line":50},2,[41,52,53],{},"-- Iceberg time travel: query the table exactly as it looked at a past snapshot\n",[11,55,57],{"id":56},"when-youll-hear-this","When You'll Hear This",[16,59,60],{},"\"We migrated our data lake to Iceberg so Snowflake and Spark can query the same tables.\" \u002F \"The Iceberg snapshot lets us time-travel back to yesterday's data.\"",[62,63,64],"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":66},[67,68,69,70],{"id":13,"depth":50,"text":14},{"id":21,"depth":50,"text":22},{"id":28,"depth":50,"text":29},{"id":56,"depth":50,"text":57},"database","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...","advanced","md","a",{},true,"\u002Fterms\u002Fa\u002Fapache-iceberg",[80,81,82,83,84],"Delta Lake","Lakehouse","Apache Parquet","Schema Evolution","Data Lake",{"title":5,"description":72},{"changefreq":87,"priority":88},"weekly",0.7,"terms\u002Fa\u002Fapache-iceberg","-tr4TJieqI2LZhl1cvNSMPS3LNpwupUquCu_bfoFW2g",[92,96,99,102,106],{"title":82,"path":93,"acronym":6,"category":71,"difficulty":94,"description":95},"\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":84,"path":97,"acronym":6,"category":71,"difficulty":94,"description":98},"\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":80,"path":100,"acronym":6,"category":71,"difficulty":73,"description":101},"\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...",{"title":81,"path":103,"acronym":6,"category":104,"difficulty":94,"description":105},"\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":83,"path":107,"acronym":6,"category":71,"difficulty":94,"description":108},"\u002Fterms\u002Fs\u002Fschema-evolution","Your data's shape never actually stays still: new fields show up, old ones get renamed, types change, and yet you've got old data sitting around in the old...",1792528060679]