Outdated SQL Server statistics often cause bad query plans, experts explain

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SQL Server's optimizer relies on statistics rather than raw data when choosing a query plan, so missing or stale statistics can lead to poor choices such as scans instead of seeks or memory spills. Each statistics object records value distribution through a header, density vector, and histogram that help estimate row counts. Automatic updates occur when enough rows change, but on very large tables they may lag or rely on small samples that miss skewed values. Growing columns like identity values or dates are especially prone to underestimates for newly added rows until statistics are refreshed. Practitioners are advised to monitor modification counters, use full-scan updates for important skewed columns, and refresh statistics after large data loads.

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