Technology Radar
Apache Iceberg is an open table format for large-scale analytical datasets that defines how data files, metadata and schemas are organized on storage systems such as S3. Having evolved significantly in recent years, it has become a foundational building block for technology-agnostic lakehouse architectures.
Iceberg is now supported by all major data platform providers — including AWS (Athena, EMR, Redshift), Snowflake, Databricks and Google BigQuery — making it a strong option for avoiding vendor lock-in. What distinguishes Iceberg from other open table formats is its openness across features and governance, unlike alternatives whose capabilities are limited or controlled by a single vendor.
From a reliability perspective, Iceberg's snapshot-based design provides serializable isolation, safe concurrent writes through optimistic concurrency and version history with rollback. These capabilities deliver strong correctness guarantees while avoiding performance bottlenecks.
While Apache Spark remains the most common engine used with Iceberg, it’s also well supported by Trino, Flink, DuckDB and others, making it suitable for a wide range of use cases, from enterprise data platforms to lightweight local analytics. Across many of our teams, Iceberg has earned strong trust as a stable, open data format; we recommend it as a default choice for organizations building modern data platforms.
Apache Iceberg is an open table format for very large analytic data sets. Iceberg supports modern analytical data operations such as record-level insert, update, delete, time-travel queries, ACID transactions, hidden partitioning and full schema evolution. It supports multiple underlying file storage formats such as Apache Parquet, Apache ORC and Apache Avro. Many data-processing engines support Apache Iceberg, including SQL engines such as Dremio and Trino as well as (structured) streaming engines such as Apache Spark and Apache Flink.
Apache Iceberg falls in the same category as Delta Lake and Apache Hudi. They all more or less support similar features, but each differs in the underlying implementations and detailed feature lists. Iceberg is an independent format and is not native to any specific processing engine, hence it's supported by an increasing number of platforms, including AWS Athena and Snowflake. For the same reason, Apache Iceberg, unlike native formats such as Delta Lake, may not benefit from optimizations when used with Spark.
