Introduction Have you ever started a bulk data load that ran lightning-fast initially, only to watch it grind to a crawl hours later? You're not alone. This is one of the most common—and most misunderstood—performance issues in Oracle databases. In this post, I'll share a real-world case study where a data load that started at 550,000 rows/hour degraded to just 40,000 rows/hour—a 93% performance drop. More importantly, I'll explain exactly why this happens and how to fix it. The Scenario Our team was loading data into a staging table as part of a nightly ETL process. The setup looked like this: Table Configuration: CREATE TABLE STG_CUSTOMER_EXTRACT ( CUSTOMER_ID NUMBER, ACCOUNT_NUMBER VARCHAR2(50), BILLING_ID VARCHAR2(30), REGION_CODE VARCHAR2(10), LOAD_DATE DATE ); -- Three indexes to support downstream queries CREATE INDEX IDX_CUSTOMER_ID ON STG_CUSTOMER_EXTRACT(CUSTOMER_ID); CREATE INDEX IDX_ACCOUNT_NUM ON STG_CUSTOMER...