Delta Lake on S3 can lead to high storage costs if not configured properly. Common mistakes often stem from misunderstandings about how Delta Lake and S3 handle data versioning. Delta Lake manages versions through transaction logs that track changes to tables. S3, on the other hand, uses object versioning that can create multiple versions of the same object when changes occur. This can cause confusion and unnecessary costs because S3 retains noncurrent versions even after Delta Lake has vacuumed old data. The result is that users end up paying for storage that should have been deleted. Storage classes in S3 also play a significant role in cost management. S3 offers several tiers, including hot, cool, cold, and archive, depending on how frequently data is accessed. While cheaper storage options sound appealing, they can lead to higher retrieval costs if not used wisely. For instance, if a lifecycle policy moves data to S3-IA after 30 days, querying older data without proper filters can lead to expensive retrieval fees. Similarly, moving data to Glacier classes can cause delays, as files need to be restored before access, which can take hours unless expedited retrieval is chosen. Data transfer costs are another area where oversight can inflate bills. When data is accessed from a different region than where it’s stored, egress fees kick in. A common oversight is routing traffic through a NAT Gateway, which incurs charges every time data is processed. If EC2 instances are in a different availability zone than the NAT Gateway, additional costs accrue. Users need to ensure that their architecture minimizes these routes to keep expenses in check.