Apache Iceberg vs Delta Lake: Choosing the Right Table Format

Apache Iceberg and Delta Lake are the two dominant open table formats for data lakehouses, both offering ACID transactions, schema evolution, and time travel on Parquet files. The feature gap has narrowed significantly since 2023, making ecosystem fit and vendor coupling the primary decision factors. Iceberg uses a hierarchical metadata model with an open REST catalog spec, enabling true multi-engine support across Spark, Flink, Trino, Snowflake, ClickHouse, and DuckDB, plus official Apache-governed SDKs in Java, Python, Rust, and Go. Delta Lake uses a flat transaction log optimized for Spark and Databricks, with Unity Catalog for governance and liquid clustering replacing traditional partitioning. UniForm allows Iceberg-compatible engines to read Delta tables in read-only mode. The recommendation: choose Iceberg for multi-engine, vendor-neutral architectures; choose Delta Lake for Databricks-centric stacks where deep integration and features like Change Data Feed and multi-table transactions matter.