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Apache Iceberg

A high-performance table format for huge analytic tables, offering snapshots, transactions and multi-engine compatibility.

Introduction

Apache Iceberg is a high-performance table format for large analytic datasets. It brings ACID snapshots, time travel, partition evolution, and a stable metadata layer to data lakes, enabling multiple engines (Spark, Flink, Trino, etc.) to safely operate on the same tables.

Key features

  • Standardized table format with versioned snapshots and atomic commits.
  • Engine interoperability across Spark, Flink, Trino and more.
  • Support for Parquet/ORC/Arrow and optimized metadata layout for fast reads.
  • Strong community governance under the Apache Software Foundation.

Use cases

  • Data lake governance and reliable table management.
  • Multi-engine analytics where different compute frameworks share data.
  • Building cloud-native data warehousing architectures.

Technical characteristics

  • Reference Java implementation with modular components and integrations.
  • Well-documented spec and production-tested implementations.
  • Compatible with S3, HDFS, GCS and other storage backends.

Comments

Apache Iceberg
Resource Info
🌱 Open Source 💾 Data 📱 Application