Hi @Willem520, thanks for reaching out to us.
Dgraph stores data in posting lists(more here). When you first bulk load the data, all posting lists are stored as complete posting lists. But when you perform mutations, many smaller part of same posting lists(called as delta postings) are formed as a result of these mutations. These parts are merged periodically(via snapshot and rollups) to form complete posting lists(and deleting deltas).
Having delta posting list helps in increasing write throughput but affects read throughput. We have recently enabled incremental rollups to stop rollups of all posting lists at once. This might be one of the reason for performance difference in first and second case.
Other reason I think of is more data to be read/scanned in second case even rollups for all posting list has been completed(as Dgraph uses Badger for storage and data is not deleted immediately from disk, but delete happens via compactions).
Hope this answers your question.