Apache Iceberg
Apache Iceberg is an open source table format that adds structure, ACID transactions, and schema evolution to large analytical datasets stored as files on object storage. It lets multiple engines read and write the same data safely, without the coordination problems of earlier data lake designs.
The table format for open data lakes
A data lake stores data as files on object storage like S3. That is cheap and flexible, but without a table format, there is no way to handle concurrent writes, schema changes, or consistent snapshots. Iceberg solves this by maintaining a metadata layer that tracks which files belong to which table version.
Iceberg supports full schema evolution, including column renames and type changes, without rewriting data. It provides time-travel queries so you can read previous table states. And it works with any engine that supports the format: Spark, Trino, Flink, DuckDB, and others.
The format has become a foundation of the lakehouse architecture, where the flexibility of a data lake meets the management capabilities of a warehouse.
How Arc handles Apache Iceberg
Arc can export its data as Apache Iceberg tables, so other engines like Spark or Trino can query Arc data through the Iceberg format. Your data stays in open Parquet underneath, and the Iceberg metadata layer makes it accessible to the broader analytical ecosystem.
Arc is a SQL-native time-series database. Open Parquet on storage you own, single Go binary, production-ready in 30 seconds.