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MongoDB offers a full-text search solution, MongoDB Atlas Search, for data hosted on MongoDB Atlas.
NoSQL systems combine document store concepts with full-text indexing solutions, which results in high-quality search solutions and produces results with better search quality. Understanding why NoSQL search results are superior will help you evaluate the merits of these systems.
What are the drawbacks of NoSQL databases? One of the most frequently cited drawbacks of NoSQL databases is that they don't support ACID (atomicity, consistency, isolation, durability) transactions across multiple documents. With appropriate schema design, single-record atomicity is acceptable for lots of applications.
Full-text search refers to searching some text inside extensive text data stored electronically and returning results that contain some or all of the words from the query. In contrast, traditional search would return exact matches.
None of the existing "NoSQL" database provides a reasonable implementation of something that could be named "fulltext search". MongoDB in particular has barely nothing so far (matching using regular expressions is not fulltext search and searching using $in or $all operators on a keyword word list is just a very poor implementation of a "fulltext search"). Using Solr, ElasticSearch or Sphinx is straight forward - an implementation and integration on the application level. Your choice widely depends on you requirements and current setup.
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