Memory-optimized tables improve performance (5-30 times) for high-performance OLTP workloads by storing data in memory and eliminating traditional locking. They excel in extreme concurrency, heavy tempdb usage, or thousands of transactions per second, requiring specific implementation steps such as memory-optimized filegroups and precise index planning. Although not suitable for all workloads, when implemented correctly for appropriate cases, they can significantly improve application performance and address complex concurrency issues.
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