Filtering with WHERE is generally faster than HAVING when you're not using aggregates.
One of the most overlooked SQL optimizations is knowing when to use WHERE versus HAVING. While both are used for filtering, they operate at different stages of the query lifecycle—WHERE filters rows before aggregation, while HAVING filters after aggregation. Choosing the wrong one can cause unnecessary compute and slow query execution.
In practice, if you're filtering non-aggregated columns, WHERE is significantly more efficient. For example, filtering region = 'West' in a sales table should be done with WHERE, not HAVING, because the database can prune rows early—before grouping and sorting.
Many beginners default to HAVING out of habit, especially in queries that also use GROUP BY. But unless you're filtering on a column like SUM(sales) > 10000, there's no need to use HAVING. Using WHERE instead will reduce I/O, speed up processing, and make better use of indexes.
Galaxy's optimizer catches improper use of HAVING and suggests restructuring your filters. Switching to WHERE can often cut runtime by 2x or more on large data sets, especially in BI dashboards and customer-facing reports where speed matters.
SELECT * FROM sales GROUP BY region HAVING region = 'West';
SELECT * FROM sales WHERE region = 'West' GROUP BY region;
Up to 2x faster in large datasets
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