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title: Why Apache Iceberg Is Not “Just Another Table Format”
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# Why Apache Iceberg Is Not “Just Another Table Format”

**[Snowflake Community](https://daily.dev/sources/snowflake_comm)** · 8 min read · 37 upvotes · 0 comments

## Summary

Apache Iceberg is a table format specification that sits between file formats (Parquet, ORC) and compute engines, solving critical failures of the Hive era: slow query planning via directory listing, silent schema corruption from position-based column tracking, and lack of safe concurrent writes. Iceberg replaces directory-based tracking with a versioned metadata tree, enabling file-level statistics for query pruning, ACID transactions via immutable snapshots with atomic commits, and metadata-only schema evolution using permanent column IDs. Unlike a traditional warehouse, Iceberg delivers warehouse-grade guarantees on open, decoupled object storage — but shifts operational responsibility (compaction, snapshot expiration) to the user. Major adoption signals include Snowflake achieving full parity with native tables, AWS S3 Tables with built-in Iceberg support, and companies like LinkedIn and Airbnb reporting significant performance and cost gains.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/snowflake/why-apache-iceberg-is-not-just-another-table-format-88bee645c0ed>

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Tags: [#big-data](https://daily.dev/tags/big-data), [#snowflake](https://daily.dev/tags/snowflake), [#data-lake](https://daily.dev/tags/data-lake), [#apache-iceberg](https://daily.dev/tags/apache-iceberg)

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