Queueable Chaining vs Batch Chunking for High-Volume Apex Processing

When a scheduled integration must process a data set that exceeds the SOQL row governor limit but remains within the documented batch ceiling, the choice between Queueable Apex with self-chaining and Batch Apex with Database.executeBatch() becomes a design trade-off rather than a simple volume check.

Queueable Apex supports complex object types and job chaining, but chaining is limited to one child job per parent in synchronous contexts, and deep chains can obscure transaction flow during debugging. Batch Apex provides explicit chunking through the start, execute, and finish lifecycle and exposes job state via AsyncApexJob, yet queuing too many batches simultaneously can trigger Concurrent Request limits.

The unresolved decision is whether the operational visibility of AsyncApexJob and the structured chunk boundaries of Batch Apex outweigh the flexibility of Queueable execute methods for a nightly job that needs conditional logic between chunks. Is the debugging cost of Queueable chaining acceptable when each transaction requires distinct parameter handling, or does the risk of Concurrent Request limits make a single Batch job the safer default?