Just Like IoT, Enterprises Have Been Using AI All Along

Query optimization is a process used by databases and data warehouses to rework user queries to deliver quick responses with minimal compute resources. It involves algorithms that sift through multiple query plan choices to make the best decision, often relying on cardinality estimates, costing, and understanding data distribution. Query optimization aligns with AI principles, using predictions to identify efficient ways to run operations. The process benefits enterprises by providing faster results, reducing compute resources, and supporting more users. As distributed systems become more prevalent, query optimization becomes even more important, considering network usage and join algorithm choices. In the future, AI techniques will continue to play a significant role in query optimization, enabling real-time adjustments and improving database performance over time.