Compared to databases, using systems that are capable of performing full-text search can often be anything other than obvious. We can search in many fields simultaneously, and the data in the index can vary from the ones provided as the values of the document fields (because of the analysis process, synonyms, abbreviations, and others). It's even worse; by default, search engines sort data by relevance—a number that indicates how similar the document is to the query. The key here is how similar. As we already discussed, scoring takes many factors into account: how many searched words were found in the document, how frequent the word was, how many terms were present in the field, and so on. This seems complicated, and finding out why a document was found and why another document is better is not easy. Fortunately, Elasticsearch has some tools that can answer these questions, and we will look at them now.