How Trino, Spark, and DuckDB each query the same Apache Iceberg table

Apache Iceberg allows multiple query engines to read the same table stored in object storage without duplicating data, with each engine differing only in how it accesses the shared metadata. Trino connects via a catalog and offers clean, straightforward SQL for interactive queries, making it well-suited for shared lakehouse environments. Spark requires additional session configuration with Iceberg extensions but is the preferred choice when queries are part of larger data pipelines involving transforms or batch writes. DuckDB provides the fastest path for local, read-only inspection by scanning Iceberg metadata files directly, though it can also attach a REST catalog for broader catalog-backed workflows. Understanding how all three engines interact with the same underlying table is essential for teams building and operating real lakehouse architectures.