Lakehouse platforms & table formats · Apache Software Foundation

Apache Iceberg

Open-source table format that adds warehouse-style transactions, schema evolution, and time travel to data-lake files.

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Apache Iceberg is an open-source table format, not a database or product: it is a specification and set of libraries that let engines like Spark, Trino, Flink, and Snowflake treat a directory of Parquet, ORC, or Avro files in a data lake as a reliable, ACID-transactional table. Iceberg tracks table state through a chain of immutable metadata and manifest files rather than by listing directories, which enables snapshot isolation, safe concurrent writes, time travel to prior snapshots, and in-place schema and partition evolution without rewriting existing data. Because Iceberg is a shared, engine-agnostic format rather than a vendor's storage layer, multiple compute engines can read and write the same tables, which is why it has become a common interchange format among lakehouse platforms including Snowflake, Databricks, Dremio, and Starburst.

At a glance

Vendor Apache Software Foundation
Pricing model Open source + paid options
Free tier Yes
Deployment Self-hosted
Open source Yes (Apache-2.0)
Best for Teams building a multi-engine lakehouse who need one open table format multiple compute engines can share.

Pricing

Free, open-source specification and libraries; no vendor pricing, though managed catalog and compute services built on Iceberg are sold separately by cloud vendors.

Pricing has not been verified yet — see the vendor's site.

Features

  • ACID transactions with snapshot isolation on data-lake files
  • Time travel and rollback to previous table snapshots
  • In-place schema evolution (add, drop, rename, reorder columns)
  • Hidden partitioning with partition evolution without rewriting data
  • Engine-agnostic: readable/writable by Spark, Trino, Flink, and more
  • Manifest-based metadata avoiding costly file-listing operations
  • Support for Parquet, ORC, and Avro file formats

Integrations

Profile last reviewed September 21, 2026

Head to head

Alternatives

Delta Lake Open-source storage format that brings ACID transactions and versioning to Parquet files on a data lake. Apache Hudi Open-source table format optimized for high-volume upserts, deletes, and incremental data-lake pipelines. Apache Paimon Open-source lake table format built for unified streaming and batch updates, originating from the Apache Flink community.

Apache Iceberg in the index now

Terms to know

Data lakehouse A storage architecture that adds warehouse-style structure and transactions directly on top of low-cost data lake storage. Data lake A storage repository that holds raw data of any format cheaply, with structure applied only when the data is read. Data modeling The practice of organizing data into entities, relationships and schemas that make it accurate and efficient to query. Apache Iceberg An open table format adding ACID transactions, schema evolution, and time travel to files stored in a data lake. Open table format A specification that adds transactions, schema management, and versioning to files stored in a data lake. Schema evolution The ability of a table to accommodate structural changes, like an added or renamed column, without breaking data.

Related guides

How to choose a lakehouse platform Choosing a lakehouse means two decisions, not one — which open table format your data sits in, and which platform manages and queries it.