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Iceberg is a high-performance format for huge analytic tables. Iceberg brings the reliability and simplicity of SQL tables to big data while making it possible for engines like Spark, Trino, Flink, Presto, Hive, and Impala to safely work with the same tables, at the same time. The core Java library that tracks table snapshots and metadata is complete, but still evolving. Current work is focused on adding row-level deletes and upserts, and integration work with new engines like Flink and Hive. The Iceberg format specification is being actively updated and is open for comment. Until the specification is complete and released, it carries no compatibility guarantees. The spec is currently evolving as the Java reference implementation changes.
Features
- Java API javadocs are available for the master
- The open table format for analytic datasets
- Iceberg is a high-performance format for huge analytic tables
- Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Spark, Trino, Flink, Presto, Hive and Impala
- Iceberg supports flexible SQL commands to merge new data, update existing rows, and perform targeted deletes
- Iceberg can eagerly rewrite data files for read performance, or it can use delete deltas for faster updates
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