What are the examples of scalable and non-scalable data structures?

Big data era, people say the big data systems must use the scalable data structures and store.

I didn't get the point here. I need some examples.

What are the good examples of (1) scalable and (2) non-scalable data structure respectively?

Can any one give me an idea on it?

If I understand correctly, scalable structures refer to structures that can grow with the input grows without concern for memory. Off the top of my head I'd imagine scalable structures such as a tree structure that can grow and search elements quickly, generally O(log(n)) even tho they're a bit more memory intensive.

Where a non scalable structure would be something like an array or any type of structure that has its memory statically allocated to it. While it takes longer to search, generally O(n) but has a predictable memory size. I hope this helps. Note that trees (or other structures that often are dynamically allocated) can be written as array based such as an array based heap that has both static memory allocation but O(log(n)) search capabilities.

It would make sense for big data to use scalable structures since the amount of data is by definition- big and they likely need to query it in an efficient way. I hope I understood your question and this helps.

StackExchange Computer Science Q#65494, answer score: 4