Snowflake table types explained

Snowflake currently offers several table types including Base/Permanent, Temporary, and External. In addition to these, four new table types were announced between 2022-2023: Dynamic, Event, Hybrid, and Iceberg tables. These new table types represent the evolution of Snowflake's table types from duration-based and location-based to use-case based. Dynamic Tables allow users to materialize query results with an input for desired lag, creating a new table that references and merges data from upstream objects on a specified schedule. They are useful for tasks like cleaning and merging data from multiple sources in recurring modeling processes. Event Tables capture information about Snowpark or stored procedure job runs, providing records generally split into severity levels (e.g., WARN, ERROR) for debugging purposes. They are beneficial for anyone developing on top of Snowflake. Hybrid Tables support both high-volume transaction workloads and single-row lookups, making them suitable for companies looking to get rid of their transactional system and use Snowflake for analytics. Iceberg Tables, named after the table format created by Netflix and now Apache open-source licensed, are useful for handling large datasets and tracking schema evolution in metadata. The decision to leverage this new table type will likely be a broader organizational discussion about how data is used and stored.