Optimize Data Loading in Dedicated SQL Pool

Quick Answer

Loading large volumes of data quickly into a dedicated SQL pool means minimizing two separate costs: the overhead of writing transaction log entries for every row, and the cost of moving data across the network once it has landed. CREATE TABLE AS SELECT is a minimally logged operation, meaning it generates far less transaction log overhead than a row-by-row INSERT, which matters enormously at scale. Partition switching complements this by letting you swap a fully loaded staging table or partition into the target table as a metadata-only operation, repointing which partition holds which data, instead of physically copying or moving the rows themselves, which is why it avoids data movement altogether. The other well-known technique for this same broader goal is using ROUND_ROBIN distribution for the initial staging table: because ROUND_ROBIN spreads rows evenly across distributions without needing to compute a hash distribution key for each row, it is the fastest way to get data into a dedicated SQL pool in the first place, before CTAS and partition switching take over to move that data into its final, properly distributed home. When a dedicated SQL pool question asks how to optimize loading large data volumes, look for answers built around minimal logging, metadata-only partition operations, and low-overhead staging distribution, rather than techniques meant for query-time performance.