[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-85070-en":3,"doc-seo-85070-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},85070,1099514067438,"River Wang","https://ap-avatar.wpscdn.com/avatar/100002539ee87300030?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780474512215547542",8,"Research & Report","GitLake Git-for-data for the Agentic Lakehouse","GitLake introduces a Git-for-data layer for an agent-first lakehouse workflow. It transforms single-table Iceberg snapshots into lakehousewide commits, branches, and merges, enabling agents to iterate on isolated branches while humans review and publish selected changes. Data pipelines execute on temporary branches and publish via a final merge, ensuring outputs are atomically visible or not produced at all. The work also shares production experience and correctness insights from a preliminary Alloy model of core abstractions.","GitLake: Git-for-data for the agentic lakehouse  \nWeiming Sheng∗ Columbia University USA  \nAldrin Montana∗ Bauplan Labs USA  \nJinlang Wang∗ University of Wisconsin-Madison USA  \nJacopo Tagliabue∗ Bauplan Labs USA  \nManuel Barros∗ Carnegie Mellon University USA  \nLuca Bigon∗ Bauplan Labs USA  \narXiv :2607 .083 19v 1 [ cs .DB] 9 Jul 2026  \nABSTRACT  \nWe present GitLake, a Git-for-data design for an agent-first lakehouse. The system lifts single-table Iceberg snapshots into lakehousewide commits, branches, and merges, letting agents work on isolated branches while humans review and publish changes. Pipelines run on temporary branches and publish through a final merge, so all outputs become visible atomically or none do. Finally, we report production lessons as well as correctness insights from a preliminary Alloy model of our core abstractions.  \nVLDB Workshop Reference Format:  \nWeiming Sheng, Jinlang Wang, Manuel Barros, Aldrin Montana, Jacopo Tagliabue, and Luca Bigon. GitLake: Git-for-data for the agentic lakehouse. VLDB 2026 Workshop: DASHSys: Systems for Data-centric Agents with Human-in-the-loop.  \nVLDB Workshop Artifact Availability:  \nThe source code, data, and/or other artifacts have been made available at [https://github.com/BauplanLabs/git_for_data](https://github.com/BauplanLabs/git_for_data).  \n1 INTRODUCTION  \nCoding agents are taking the software engineering industry by storm, both when humans and agents write code together in a tight feedback loop and when agents in a ReAct loop [13] continuously hill-climb toward a task. Version control systems such as Git lie atthe core of both patterns as they allow developers to incrementally develop software, using commits as intermediate checkpoints. Commits support time-travel for debugging and reverting code, and provide a unit of concurrent collaboration. However, agentic adoption in the data analytics domain lags behind the rest ofthe industry. The lakehouse is the de facto standard OLAP for analyticsand AI workloads [11]; however, the affordances in traditional OLAP systems make agents unsafe [9] .  \nWe share the design of GitLake, the Git-for-data layer inside Bauplan’s lakehouse platform. As labor shifts from writing code to verifying and approving changes, correctness in the face of untrusted actors becomes non-negotiable [4] . GitLake induces a natural division of labor between humans and agents: agents can explore  \n∗ All authors contributed equally and are listed ORDER BY AGE ASC. JT is the corre[sponding author and PI on the project: mailto:jacopo.tagliabue@bauplanlabs.com](sponding author and PI on the project: mailto:jacopo.tagliabue@bauplanlabs.com). This work is licensed under the Creative Commons BY-NC-ND 4.0 International License. Visit [https://creativecommons.org/licenses/by-nc-nd/4.0/ to view a copy of](https://creativecommons.org/licenses/by-nc-nd/4.0/ to view a copy of)[ ](https://creativecommons.org/licenses/by-nc-nd/4.0/ to view a copy of)[this license. For any use beyond those covered by this license](this license. For any use beyond those covered by this license), [obtain permission by](obtain permission by)[emailing info@vldb.org. Copyright](emailing info@vldb.org. Copyright) is held by the owner/author(s). Publication rights licensed to the VLDB Endowment.  \nProceedings of the VLDB Endowment. ISSN 2150-8097 .  \nand propose changes on isolated branches, while humans review and approve only what should be published to production. The core abstractions are obtained by “porting” Git primitives to OLAP. By reusing familiar concepts, users quickly learn how to leverage the APIs to develop data pipelines collaboratively and time-travel toa previous state of the lake. We summarize our contributions as follows:  \n(1) we motivate Git-like abstractions in agentic data workflows through the lens of production workloads. As of today, Bauplan has run millions of jobs across hundreds of thousands of data branches (Section 5), making it, to our knowledge, one o","cbCaip9tFvgZCg4e","https://ap.wps.com/l/cbCaip9tFvgZCg4e","pdf",2032520,1,4,"English","en",105,"# Introduction\n# Git: From Code to Data","[{\"question\":\"What problem does GitLake address in agentic data analytics?\",\"answer\":\"It targets the gap where agentic adoption lags in data analytics because traditional lakehouse/OLAP affordances can make agent behavior unsafe for correctness and collaboration.\"},{\"question\":\"How does GitLake map Git concepts to lakehouse data?\",\"answer\":\"It “ports” Git primitives—commits, branches, and merges—onto lakehouse operations by lifting single-table Iceberg snapshots into lakehousewide commits and collaborative branches.\"},{\"question\":\"How do pipelines avoid partial or inconsistent outputs in GitLake?\",\"answer\":\"Pipelines run on temporary branches and publish through a final merge, so all outputs become visible atomically or none do.\"}]",1784200805,10,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"gitlake-git-for-data-for-the-agentic-lakehouse","",{"@graph":35,"@context":84},[36,52,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":21},"https://docshare.wps.com/document/gitlake-git-for-data-for-the-agentic-lakehouse/85070/",{"url":51,"name":13,"@type":53,"author":54,"headline":13,"publisher":56,"fileFormat":59,"inLanguage":23,"description":14,"dateModified":60,"datePublished":61,"encodingFormat":59,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":55},"Person",{"url":40,"name":57,"@type":58},"DocShare","Organization","application/pdf","2026-07-17","2026-07-16",true,{"@type":64,"interactionType":65,"userInteractionCount":20},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"What problem does GitLake address in agentic data analytics?","Question",{"text":74,"@type":75},"It targets the gap where agentic adoption lags in data analytics because traditional lakehouse/OLAP affordances can make agent behavior unsafe for correctness and collaboration.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"How does GitLake map Git concepts to lakehouse data?",{"text":79,"@type":75},"It “ports” Git primitives—commits, branches, and merges—onto lakehouse operations by lifting single-table Iceberg snapshots into lakehousewide commits and collaborative branches.",{"name":81,"@type":72,"acceptedAnswer":82},"How do pipelines avoid partial or inconsistent outputs in GitLake?",{"text":83,"@type":75},"Pipelines run on temporary branches and publish through a final merge, so all outputs become visible atomically or none do.","https://schema.org",{"og:url":51,"og:type":86,"og:title":13,"og:site_name":57,"og:description":14},"article",{"robots":88,"canonical":51},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":91},[92,96,100,104,109,114,119,122,127,130,133],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":21,"doc_module":4,"doc_module_name":45,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":45,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":45,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":45,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":45,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":45,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":28,"doc_module":4,"doc_module_name":45,"category_name":131,"show_sort_weight":28,"slug":132},"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":45,"category_name":135,"show_sort_weight":105,"slug":136},19,"General","general"]