--- title: Revolutionizing Data Management with Apache Iceberg and... description: Open table formats like Apache Iceberg, Delta Lake, and Apache Hudi are transforming large-scale data management by enabling ACID transactions, schema... canonical: https://daily.dev/posts/revolutionizing-data-management-with-apache-iceberg-and-open-table-formats-cpkc34qhk twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Revolutionizing Data Management with Apache Iceberg and Open Table Formats | daily.dev og:description: Open table formats like Apache Iceberg, Delta Lake, and Apache Hudi are transforming large-scale data management by enabling ACID transactions, schema... og:url: https://daily.dev/posts/revolutionizing-data-management-with-apache-iceberg-and-open-table-formats-cpkc34qhk og:image: https://api.daily.dev/og/posts/CPKc34qhK.png og:image:alt: Revolutionizing Data Management with Apache Iceberg and Open Table Formats og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Revolutionizing Data Management with Apache Iceberg and Open Table Formats **[Collections](https://daily.dev/sources/collections)** · 2 min read · 3 upvotes · 0 comments ## Summary Open table formats like Apache Iceberg, Delta Lake, and Apache Hudi are transforming large-scale data management by enabling ACID transactions, schema evolution, and time travel on object storage. Apache Iceberg v3 introduces deletion vectors, row lineage, and support for new data types, while offering 6-level data elimination that reduces I/O by 99.8%. DuckDB's proposed DuckLake format aims to improve performance through metadata optimization, though it has received mixed industry feedback. These formats promote vendor-neutral architectures that decouple storage from compute, though challenges remain for real-time streaming workloads requiring sub-second latency. ## Content Open table formats such as Apache Iceberg, Delta Lake, and Apache Hudi are reshaping the landscape of large-scale data management by introducing capabilities like ACID transactions, schema evolution, and time travel on object storage systems. Among these, Apache Iceberg stands out as a leading solution for analytics workloads due to its interoperability across various compute engines, transforming raw object storage into structured, queryable datasets. The integration with Amazon S3's new features, including S3 Express and conditional writes, further enhances traditional ETL processes, enabling the ability to write once and query across multiple platforms. This represents a shift toward scalable, vendor-neutral architectures that effectively decouple storage from compute. Recent developments have seen industry reactions to DuckDB's proposal for DuckLake—a metadata-driven table format that aims to redesign the Lakehouse architecture by reducing storage round trips. This approach offers promising performance improvements but has received mixed feedback. Some, like AWS engineers, are enthusiastic about the performance gains, while others, including Snowflake's Russell Spitzer, question the generality of SQL for metadata management. Meanwhile, Apache Iceberg community members assert that existing API enhancements and caching strategies are already addressing similar challenges. With its latest version, Apache Iceberg v3 brings about significant enhancements, integrating deletion vectors for improved row-level delete performance, row lineage for incremental processing, and supporting new data types like semi-structured VARIANT and geospatial data. These improvements facilitate seamless interoperability between Delta Lake and Iceberg formats, allowing users to work across both systems without the need for data rewrites. The updates tackle previous performance bottlenecks related to delete files, enable efficient change tracking, and provide better support for complex data types. In the realm of real-time analytics, Apache Iceberg delivers robust capabilities through partitioning, sorting, and compaction, offering a 6-level data elimination system that can drastically reduce I/O operations by 99.8%. However, it faces challenges in streaming workloads, such as dealing with small file issues, metadata growth, compaction performance, and concurrent writer conflicts. While Iceberg handles batch analytics with latencies ranging from 5-30 seconds effectively, real-time applications requiring sub-second responses benefit from complementary platforms designed for high-frequency processing and long-term data storage. In summary, open table formats are redefining data management by promoting scalable architectures that emphasize interoperability and efficiency. As these systems evolve, they hold the potential to further optimize analytics and streamline data handling processes across diverse environments. ## Similar posts on daily.dev - [Don’t just attend KubeCon \+ CloudNativeCon, Merge Forward your experience\!](https://daily.dev/posts/don-t-just-attend-kubecon-cloudnativecon-merge-forward-your-experience--l0rpp73x8) · CNCF · 1 upvotes · 0 comments - [Announcing H2 2026 KCDs](https://daily.dev/posts/announcing-h2-2026-kcds-m96goajm1) · CNCF · 1 upvotes · 0 comments - [Two months of Open Community Groups](https://daily.dev/posts/two-months-of-open-community-groups-asf52zhbs) · CNCF · 0 upvotes · 0 comments - [CNCF Unveils Schedule for KubeCon \+ CloudNativeCon Europe 2026](https://daily.dev/posts/cncf-unveils-schedule-for-kubecon-cloudnativecon-europe-2026-ikhcoa5cb) · CNCF · 2 upvotes · 0 comments - [CNCF Debuts KubeCon \+ CloudNativeCon Japan 2026 Schedule](https://daily.dev/posts/cncf-debuts-kubecon-cloudnativecon-japan-2026-schedule-xp5pyudub) · CNCF · 1 upvotes · 0 comments --- Tags: [#aws](https://daily.dev/tags/aws), [#data-engineering](https://daily.dev/tags/data-engineering), [#data-lake](https://daily.dev/tags/data-lake), [#apache-iceberg](https://daily.dev/tags/apache-iceberg) [View this post on daily.dev](https://daily.dev/posts/revolutionizing-data-management-with-apache-iceberg-and-open-table-formats-cpkc34qhk) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Revolutionizing Data Management with Apache Iceberg and Open Table Formats","url":"https://daily.dev/posts/revolutionizing-data-management-with-apache-iceberg-and-open-table-formats-cpkc34qhk","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/revolutionizing-data-management-with-apache-iceberg-and-open-table-formats-cpkc34qhk"},"datePublished":"2025-06-04T14:06:35.657Z","dateModified":"2025-06-05T11:29:52.472Z","description":"Open table formats like Apache Iceberg, Delta Lake, and Apache Hudi are transforming large-scale data management by enabling ACID transactions, schema...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/c4bb01468e896026b6596fbe1fd94c52?_a=AQAEulh","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/c4bb01468e896026b6596fbe1fd94c52?_a=AQAEulh","isAccessibleForFree":true,"articleSection":"Collections","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Collections","logo":"https://media.daily.dev/image/upload/s--fk_6ycEi--/f_auto,q_auto/v1780996001/logos/collections?_a=BAMAMiWQ0","url":"https://daily.dev/sources/collections"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/revolutionizing-data-management-with-apache-iceberg-and-open-table-formats-cpkc34qhk","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":3},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"aws,data-engineering,data-lake,apache-iceberg","timeRequired":"PT2M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Collections","item":"https://daily.dev/sources/collections"},{"@type":"ListItem","position":3,"name":"Revolutionizing Data Management with Apache Iceberg and Open Table Formats"}]} ```