Data structures are use-case dependent

A data structure organizes your data in a specific way, allowing for efficient access, modification, deletion, and analysis.

There is no one-size-fits-all data structure—each has strengths and weaknesses depending on the use case. Some perform better in certain scenarios than others. For example, arrays are ideal when your application requires frequent look-up operations due to their O(1) random access time (250203120334).

On the other hand, if insertions and deletions occur more often than lookups, a linked list can offer better performance since inserting or deleting nodes does not require shifting elements like in an array.

For a balance of fast lookups, insertions, and deletions, you might consider using a hash table, which provides near O(1) average-time complexity for these operations at the cost of additional memory.

Many more data structures exist, each designed for different use cases. You don’t need to master them all at once, but it’s important to be aware of their existence. When you encounter a situation where your current data structure isn’t efficient, take the time to explore alternatives.

The more you know, the more creative you can be.