Introduction
Performing bulk updates in SQL Server can be a resource-intensive operation, particularly when dealing with large datasets. The efficiency of such operations is influenced by various factors, including batch size, disk I/O, memory usage, CPU utilization, and locking behavior. Larger batch sizes can reduce execution time by processing more records in fewer iterations, but they may also introduce challenges such as higher memory consumption, increased locking contention, and greater I/O pressure, which could negatively impact overall system performance.
This article explores the impact of different batch sizes on SQL Server performance during update operations. We conduct tests