It's not it's primary function and you can find many questions here on SO where people struggle with lack of some functionality they had in Elasticksearch - the purpose built fulltext search engine. However, because they are not utilizing indexes optimally, those could quickly become problematic once you need blazing fast results for autocomplete suggestions, for example. Use the text query operator to perform text searches on a collection with a text index. Mongodb added support for full text search. These searches are easy to use and can work well on small data sets. In MongoDB, a similar search can be done using the $regex operator. SELECT * FROM menus WHERE item LIKE "%pasta%" ![]() In a SQL database, a search on a text field in a record is usually done using a LIKE operator. Other advanced techniques can be used to perform fuzzy searches. The regex operator allows for partial-text search and the text operator makes a full-text search possible, but enabling fuzzy search is a little more complicated. Text search in MongoDB is fairly straight-forward. In this case, MongoDB can use an index and hence the query is always efficient. The Knuth-Morris-Pratt algorithm looks for all instances of a matching character, increasing the speed for multiple matches in a string. A simple text search needs to allow for a small typo, a missing space, and other errors. Explaining the full text search performance is quite straightforward. The Rabin-Karp algorithm, which looks for matching substrings, is fast and easy to implement. Some algorithms exist to increase the speed of those searches if the text to be searched is more significant. Those expressions represent a search pattern and are supported by most modern programming languages. Those searches will be performed character per character and can be relatively slow.Īnother technique often used for string searches is the use of regular expressions. ![]() ![]() String searches are algorithms that search for consecutive characters in a larger text field.
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