Sometimes there are properties in the document with unstructured text, like newspaper articles, blog posts, or book abstracts. The inverted index is easy to build and is similar to data structures search engines use.
Such document structures can help in various complex search patterns, like common word detection, full-text searches, or document similarity searches, using humming distance or l2distance algorithms. Inverted indexes are useful when the number of keywords is not too large and when the existing data is either totally immutable or rarely changed, but frequently searched.
This post and Maria’s MSSQLTips post both cover the high-level concept, focusing on tradeoffs between different data models. I like this sort of idea a lot and like telling people that sometimes, the right answer in a relational database involves thinking backwards.