---
title: "Open Table Formats Explained: Iceberg vs. Delta vs. Hudi"
description: "Open table formats add metadata layers over Parquet or ORC files in object storage, enabling ACID transactions, schema evolution, time travel, and database-like consistency for data lakes. Apache Iceberg uses manifests and manifest lists in a metadata tree, supports partition evolution without rewriting existing files, and creates immutable snapshots for auditing, rollback, and reproducible queries. Delta records atomic writes in an ordered transaction log with checkpoints and is closely associated with Spark, while Hudi uses record-level indexes for frequent updates, change-data-capture, and near-real-time ingestion. All three share core capabilities but differ in partition evolution, update and delete strategies, and multi-engine support; Parquet and ORC remain file formats rather than table formats. The overview recommends scheduled compaction, metadata maintenance, health monitoring, and a production-volume proof of concept when selecting a format."
---

# Open Table Formats Explained: Iceberg vs. Delta vs. Hudi

[Databricks](https://yomu.fyi/company/databricks) · Databricks Staff · Aug 25, 2026

**Type:** Explainer

## Summary

Open table formats add metadata layers over Parquet or ORC files in object storage, enabling ACID transactions, schema evolution, time travel, and database-like consistency for data lakes. Apache Iceberg uses manifests and manifest lists in a metadata tree, supports partition evolution without rewriting existing files, and creates immutable snapshots for auditing, rollback, and reproducible queries. Delta records atomic writes in an ordered transaction log with checkpoints and is closely associated with Spark, while Hudi uses record-level indexes for frequent updates, change-data-capture, and near-real-time ingestion. All three share core capabilities but differ in partition evolution, update and delete strategies, and multi-engine support; Parquet and ORC remain file formats rather than table formats. The overview recommends scheduled compaction, metadata maintenance, health monitoring, and a production-volume proof of concept when selecting a format.

## Context

Object storage provides inexpensive, scalable storage and separates storage from compute, but it does not natively provide tables, schemas, transactions, or consistency. Analytics on unstructured data-lake files can therefore face corrupted concurrent writes, expensive updates and deletes, and uncertainty about which files represent the current table state.

## Approach / What changed

The overview explains how Apache Iceberg, Delta Lake, and Apache Hudi manage metadata over object-storage files. It compares their transaction, schema-evolution, partition-evolution, update and delete, and engine-support characteristics, then describes Iceberg snapshots and metadata trees, Delta transaction logs, Hudi record-level indexes, maintenance practices, and proof-of-concept selection criteria.

## Takeaways

- Iceberg uses manifest files and manifest lists to track table data files and prune irrelevant files before scanning; partition evolution can change how new data is partitioned without rewriting existing files.
- Delta Lake records adds, removes, and metadata changes in an ordered append-only transaction log, with checkpoint files that summarize the log for faster reads.
- Hudi is optimized for frequent record-level updates and streaming ingestion by maintaining indexes that locate the file containing a given record, making it suited to change-data-capture pipelines.

**Tags:** [Architecture](https://yomu.fyi/topic/architecture), [Data Pipelines](https://yomu.fyi/topic/data-pipelines), [Migrations](https://yomu.fyi/topic/migration), [Performance](https://yomu.fyi/topic/performance), [Streaming](https://yomu.fyi/topic/streaming)

- Source: [Databricks](https://www.databricks.com/blog/open-table-formats)
- Source URL: https://www.databricks.com/blog/open-table-formats
- Ingested by Yomu: 2026-08-30T12:35:59.174Z

[Read original post](https://www.databricks.com/blog/open-table-formats)