In a state-managing javascript framework (eg: React), if you have a collection of objects to store in state, which is the more useful and/or performant dataset type to hold them all, an object or an array? Here are a few of the differences I can think of that might come up in using them in state:
Referencing entries:
With objects you can reference an entry directly by its key, whereas with an array you would have to use a function like dataset.find(). The performance difference might be negligible when doing a single lookup on a small dataset, but I imagine it gets larger if the find function has to pore over a large set, or if you need to reference many entries at once.
Updating dataset:
With objects you can add new entries with {...dataset, [newId]: newEntry}, edit old entries with {...dataset, [id]: alteredEntry} and even edit multiple entries in one swoop with {...dataset, [id1]: alteredEntry1, [id2]: alteredEntry2}. Whereas with arrays, adding is easy [...dataset, newEntry1, newEntry2], but to edit you have to use find(), and then probably write a few lines of code cloning the dataset and/or the entry for immutability's sake. And then for editing multiple entries it's going to either require a loop of find() functions (which sounds bad for large lists) or use filter() and then have to deal with adding them back into the dataset afterwards.
Deleting
To delete a single entry from the object dataset you would do delete dataset[id] and for multiple entries you would either use a loop, or a lodash function like _.omit(). To remove entries from an array (and keep it dense) you'd have to either use findIndex() and then .slice(index, 1), or just use filter() which would work nicely for single or multiple deletes. I'm not sure about the performance implications of any of these options.
Looping/Rendering: For an array you can use dataset.map() or even easily render a specialized set on the fly with dataset.filter() or dataset.sort(). For the object to render in React you would have to use Object.values(dataset) before running one of the other iteration functions on it, which I suppose might create a performance hit depending on dataset size.
Are there any points I'm missing here? Does the usability of either one depend perhaps on how large the dataset is, or possibly how frequent the need to use "look up" operations are? Just trying to pin down what circumstances might dictate the superiority of one or the other.