The short answer is: for INNER JOINs, usually no; for OUTER JOINs, APPLY, and similar constructs, yes.
For inner joins, SQL Server’s optimizer is generally free to reorder joins because they are logically commutative and associative. However, that freedom is not absolute and can be constrained by factors such as join hints, query shape, cardinality estimation errors, and the optimizer’s internal search-space pruning.
So where did this question originate?
In earlier versions of SQL Server, the cost model and cardinality estimation were less sophisticated than they are today. In some cases, this caused the optimizer to choose a nested loops join with a poor driving input—such as selecting a large table as the outer input—leading to millions of repeated probes into the inner input. When this happened, query performance could degrade significantly.
These problems can still occur today, most commonly when table statistics are stale or inaccurate. In many cases, the correct fix is not to rewrite the query or immediately reach for a FORCE ORDER hint, but to ensure that statistics are up to date so the optimizer has accurate information to work with. That said, statistics alone are not always sufficient; parameter sniffing, data skew, and predicate correlation can still lead to suboptimal plans even with fresh statistics.
The modern optimizer is far more capable than its predecessors, but it is not infallible. It operates using cost estimates and heuristics, and when those estimates are wrong, join order and plan shape can still have a measurable impact on performance.
So, should you care about join order anymore?
Yes, not because you need to manually control it, but because thinking about joins order forces you to understand your data. Taking the time to reason about table sizes, row counts, and filtering logic helps you validate your mental model of how the query should behave.
Writing a query with an expected driving table in mind and then seeing the execution plan align with that expectation is a powerful confirmation that you understand both the code and the data. That habit alone makes you a better SQL developer.