We all know that, while reading a book, indexes are very important. When we try to search for a topic in the book, we scroll through the index page. If the topic is found in the index, then we go to the specific page number for that topic. But there is a drawback here. We are using additional pages for the sake of this indexing. Similarly, MongoDB needs to go through all the documents whenever we query for something. If the document stores indexes for important fields, it can give us data quickly. At the same time, we should remember that extra space is required for storing indexes.
In computing, a B-tree is an important data structure for implementing indexing because it can categorize nodes. By traversing that tree, we can find the data we need in fewer steps. We can create an index using the createIndex function provided by MongoDB...
