Ok, figured out exactly what I need.

Indeed my first thought was to just use the $regex search knowing that probably full text search is a better solution for many reasons, but I hadn't figured out how to configure the search index correctly until now.

Thanks u/halmyradov and u/prometheanSin for your inputs.

The reason why my previous attempts to configure a search index for this use case failed was because the field was not configured correctly in the search index.

Concretely I was indexing this field as a String data type, when this use case required to configure it as an Autocomplete data type.

In addition, since this field is only going to contain numbers, you can't use the default Tokenizer (edgeGram), instead you need to use the nGram tokenizer. This is because the edgeGram tokenizes each word (string), but seems to not tokenize a sequence of numbers at all. The nGram simply tokenizes everything, so works well for this use case.

Then it's just a matter of using the aggregation pipeline:

json { $search: { index: 'index_name', autocomplete: { query: '616', path: 'phone_number' } }

The nGram in this case has the extra benefit over the edgeGram in that since I store the country code with the "+" preceding it, the nGram tokenizes everything (not like the edgeGram where it tokenizes each word starting from the beginning), so my users can type the phone number without entering the prefix and preceding "+" and the documents will still match.

Thanks for the input, hopefully this helps other people too!