A data architect is evaluating Delta Lake's versioning and time travel features for auditing purposes, needing to maintain a complete history of all valid street addresses in the customers table.

The architect proposes using a Type 1 table (overwriting records and relying on time travel for auditing), while a data engineer advocates for a Type 2 table for better performance and scalability.

What key factor should influence this decision?

Exam-Like

Data corruption can occur if a query fails in a partially completed state because Type 2 tables require setting multiple fields in a single update.

15.3%

Shallow clones can be combined with Type 1 tables to accelerate historic queries for long-term versioning.

16.0%

Delta Lake time travel cannot be used to query previous versions of these tables because Type 1 changes modify data files in place.

23.7%

Delta Lake time travel does not scale well in cost or latency to provide a long-term versioning solution.

45.0%

Databricks Certified Data Engineer - Professional