A data engineer has created a 'transactions' Delta table on Databricks that should be used by the analytics team. The analytics team wants to use the table with another tool which requires Apache Iceberg format.
What should the data engineer do?
A.
Require the analytics team to use a tool which supports Delta table.
B.
Create an Iceberg copy of the 'transactions' Delta table which can be used by the analytics team.
C.
Convert the 'transactions' Delta to Iceberg and enable uniform so that the table can be read as a Delta table.
D.
Enable uniform on the transactions table to 'iceberg' so that the table can be read as an Iceberg table.
Correct:
D - This is the proper approach using Delta Lake UniForm. By setting the table property 'delta.universalFormat.enabledFormats' = 'iceberg' (along with 'delta.enableIcebergCompatV2' = 'true'), the Delta table automatically generates Iceberg metadata asynchronously. The table remains a fully functional Delta table for the data engineer, while Iceberg clients used by the analytics team can read it as if it were a native Iceberg table, all without duplicating data.
UniForm is specifically designed for this exact scenario — enabling interoperability between Delta Lake and other formats (Iceberg, Hudi) without abandoning Delta's advantages.
https://docs.databricks.com/aws/en/delta/uniform
You must set the following table properties to enable Iceberg reads:
'delta.enableIcebergCompatV2' = 'true'
'delta.universalFormat.enabledFormats' = 'iceberg'
Enable Uniform in the Delta table allows to read it as an Iceberg table. A single copy of the data files serves multiple formats. https://docs.databricks.com/aws/en/delta/uniform
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