How do many-to-many joins affect performance?

< 1 min read

Many-to-many joins affect performance because they increase data duplication in the result set.
In one project, joining two large fact tables without proper filtering created a huge intermediate dataset.
This increased memory usage and slowed down query execution.
It also caused incorrect aggregations due to duplicated records.
The query execution plan showed high cost on the join operation.
We resolved it by introducing a bridge table and applying proper filters.
Pre-aggregating data before join also improved performance.
So many-to-many joins increase complexity, processing time, and risk of data inflation.

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