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Editorial Team
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Editorial Team
Asked: May 20, 20262026-05-20T15:36:46+00:00 2026-05-20T15:36:46+00:00

When to use hashmaps or treemaps? I know that I can use TreeMap to

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When to use hashmaps or treemaps?

I know that I can use TreeMap to iterate over the elements when I need them to be sorted.
But is just that? There is no optimization when I just want to consult the maps, or some optimal specific uses?

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  1. Editorial Team
    Editorial Team
    2026-05-20T15:36:47+00:00Added an answer on May 20, 2026 at 3:36 pm

    Hashtables (usually) perform search operations (look up) bounded within the complexity of O(n)<=T(n)<=O(1), with an average case complexity of O(1 + n/k); however, binary search trees, (BST’s), perform search operations (lookup) bounded within the complexity of O(n)<=T(n)<=O(log_2(n)), with an average case complexity of O(log_2(n)). The implementation for each (and every) data structure should be known (by you), to understand the advantages, drawbacks, time complexity of operations, and code complexity.

    For example, the number of entries in a hashtable often have some fixed number of entries (some part of which may not be filled at all) with lists of collisions. Trees, on the other hand, usually have two pointers (references) per node, but this can be more if the implementation allows more than two child nodes per node, and this allows the tree to grow as nodes are added, but may not allow duplicates. (The default implementation of a Java TreeMap does not allow for duplicates)

    There are special cases to consider as well, for example, what if the number of elements in a particular data structure increases without bound or approaches the limit of an underlying part of the data structure? What about amortized operations that perform some rebalancing or cleanup operation?

    For example, in a hashtable, when the number of elements in the table become sufficiently large, and arbitrary number of collisions can occur. On the other hand, trees usually require come re-balancing procedure after an insertion (or deletion).

    So, if you have something like a cache (Ex. the number of elements in bounded, or size is known) then a hashtable is probably your best bet; however, if you have something more like a dictionary (Ex. populated once and looked up many times) then I’d use a tree.

    This is only in the general case, however, (no information was given). You have to understand process that happen how they happen to make the right choice in deciding which data structure to use.

    When I need a multi-map (ranged lookup) or sorted flattening of a collection, then it can’t be a hashtable.

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