Iceberg: From silo to interoperability
Every database used to own its data, which worked when organizations had one analytics engine. Today's data teams often combine Apache Spark™, BigQuery, Gemini Enterprise Agent Platform, Snowflake (including Snowflake's CoCo and CoWork) and other services depending on the job — often within the same pipeline.
This created a dichotomy — choose flexibility or consistency:
Let every team use its preferred engine and replicate data across systems, introducing redundancy, inconsistency and risk.
Force everyone through one engine and sacrifice the specialization and autonomy that multi-engine architectures provide.
