What are benefits of building an Iceberg Lakehouse, over a SQL RDBMS?

It's worth clarifying that Apache Iceberg isn't a replacement for SQL as a query language, you still use SQL to query Iceberg tables.

Within Zetaris, Iceberg acts as a high-performance, open storage layer that gives you warehouse-like capabilities without the lock-in or cost of a traditional database. Here are the key advantages:

1. Engine-agnostic and no vendor lock-in 
   Iceberg is 100% open source and not dependent on any individual tool or data lake engine. All applications have equal access, and processing is not tied to any specific engine, so Spark, Trino, Presto, Hive, Flink, and others can all read from and write to the same Iceberg tables simultaneously. In Zetaris, this means your data can be processed by whichever compute engine is most efficient for a given workload, without migrating or copying data.
2. Full ACID transactions at scale 
   Iceberg tables ensure full ACID compliance by managing data changes to prevent partial writes and conflicting updates, tables remain consistent and reliable even when multiple users or systems are reading and writing data simultaneously. Traditional data lakes (raw files) don't provide this, which creates data reliability problems at scale.
3. Schema evolution without disruption 
   Schema drift is mostly addressed, adding a column won't bring back "zombie" data, columns can be renamed and reordered, and schema changes never require rewriting your table. In a traditional SQL database, schema changes can be risky and require downtime or complex migration scripts. With Iceberg inside Zetaris, your pipelines and reports keep working as your data evolves.
4. Time travel and version rollback 
   Time travel enables reproducible queries that use exactly the same table snapshot, or lets users easily examine changes. Version rollback allows users to quickly correct problems by resetting tables to a good state. This is valuable for auditing, debugging, and regulatory compliance, capabilities that are complex and expensive to replicate in traditional SQL databases.
5. Intelligent partitioning and query performance 
   Iceberg handles the tedious and error-prone task of producing partition values for rows in a table and skips unnecessary partitions and files automatically, no extra filters are needed for fast queries, and table layout can be updated as data or queries change. This means faster queries without requiring end users or developers to manually manage partitioning logic.
6. Seamless data migration and replication in Zetaris 
   Zetaris provides an easy interface for users to migrate data into Iceberg lake warehouses, and Zetaris Iceberg replication helps organisations maintain high levels of data protection and resilience through incremental, snapshot-based replication  meaning only changes since the last cycle are replicated, minimising data transfer overhead.

In summary, Apache Iceberg gives you the reliability and flexibility of a modern data warehouse, but built on open standards and open storage, meaning lower cost, no lock-in, and the freedom to evolve your architecture over time. Within Zetaris, it becomes the persistent, governed storage layer that complements the platform's live data federation capabilities.