# table format Published articles for table format. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Apache Iceberg Architecture Explained DevFeed: [Apache Iceberg Architecture Explained]() Original publisher: [Read original article]() Published: 2026-10-16T08:00:04Z Content type: article Language: en Sources: [Starburst Data]() Topics: [Apache Iceberg](), [parquet](), [data lake](), [table-partitioning](), [Amazon S3]() Tags: [2](), [3](), [analytics](), [apache](), [apache-iceberg](), [apache-iceberg-architecture](), [architecture](), [format](), [high-performance](), [iceberg](), [object](), [object-storage](), [open](), [performance](), [storage](), [table](), [table-format]() ### AI overview Apache Iceberg tracks tables through a catalog pointer to immutable metadata and data files, rather than inferring table contents from directory layouts. Reads use snapshot and manifest statistics to prune files; writes create new files and metadata, then use an optimistic, atomic catalog pointer swap. This supports concurrent engine access, snapshots and time travel, while row level deletes and updates use delete files. The document distinguishes v2 position and equality deletes from v3 deletion vectors, which replace position deletes, and notes v3's VARIANT type and other additions. Engine and catalog compatibility must be checked before upgrading. Ongoing maintenance--compaction, snapshot expiration, orphan file removal and manifest optimization--helps control small file fragmentation, metadata growth and storage costs. ### Source excerpt Apache Iceberg is an open table format designed for high-performance analytics running on object storage. ... ## Apache Iceberg vs Apache Parquet: Table Format or File Format? DevFeed: [Apache Iceberg vs Apache Parquet: Table Format or File Format?]() Original publisher: [Read original article]() Author: Alex Merced Published: 2026-10-12T19:19:33Z Content type: article Language: en Sources: [Dremio]() Topics: [Apache Iceberg](), [parquet]() Tags: [apache](), [apache-iceberg](), [apache-parquet](), [data-lakehouse](), [dremio-blog-open-data-insights](), [format](), [table](), [table-format]() ### AI overview Apache Iceberg and Apache Parquet serve different layers in an analytics data stack. Parquet organizes data within individual files, while Iceberg tracks table membership, snapshots, schema and partition evolution, and atomic commits. Using both lets query engines prune files through Iceberg metadata and skip data within files through Parquet statistics. ### Source excerpt Iceberg is a table format and Parquet is a file format. They are different layers of one stack, not alternatives, and an Iceberg table contains Parquet files. The post Apache Iceberg vs Apache Parquet: Table Format or File Format? appeared first on Dremio. ## What is DuckLake? The New Open Table Format Explained DevFeed: [What is DuckLake? The New Open Table Format Explained]() Original publisher: [Read original article]() Author: Emily Lucek Published: 2025-08-21T16:00:00Z Content type: article Language: en Sources: [Estuary]() Topics: [Apache Iceberg](), [Test-driven development](), [parquet](), [Amazon S3 Tables]() Tags: [amazon-s3](), [analytics](), [apache](), [apache-iceberg](), [component](), [ducklake](), [format](), [motherduck](), [table-format](), [what-is]() ### AI overview This guide explains DuckLake, an open table format that stores metadata in a SQL database while keeping data in object storage. It describes its architecture, ACID transactions, schema evolution, snapshots, security, implementation options, and comparisons with Apache Iceberg and Delta Lake. The article also covers analytical use cases, MotherDuck hosting, data pipeline integration, migration, and planned features. ### Source excerpt DuckLake is the latest open table format. Learn how it stands out from Iceberg, Delta Lake, and others, and try it out for yourself. ## Explaining Data Lakes, Lakehouses, Table Formats and Catalogs DevFeed: [Explaining Data Lakes, Lakehouses, Table Formats and Catalogs]() Original publisher: [Read original article]() Author: Dani Pálma Published: 2024-06-27T09:27:35Z Content type: article Language: en Sources: [Estuary]() Topics: [Apache Iceberg](), [data lake](), [deltalake](), [Snowflake streaming data architecture](), [table-partitioning](), [semantic-layer](), [ML model versioning](), [Amazon S3 Tables](), [Parquet files in Amazon S3]() Tags: [apache-iceberg](), [data](), [data-engineers](), [data-lakes](), [formats](), [table-format]() ### AI overview This article explains how data lakes and lakehouses use open table formats, metadata catalogs, and compute engines. It compares Apache Iceberg, Delta Lake, and Apache Hudi, then discusses catalog architecture, interoperability, governance, and query engines such as Trino and DuckDB. ### Source excerpt Explaining Data Lakes, Data Lakehouses, Table Formats and Catalogs. This article aims to demystify the complexity around how these terms relate to each other to help Data Engineers navigate the scene.