• Fuzzy matching
• Good at searching for text in a document db or unstructured data
• Is essentially a highly-indexed database
• Ranks results based on how close they are to the query
• Filtering data
• Good for unstructured data
• Create reverse- indexes on fields in the DB to search for them

Elasticsearch stores documents, indexes, mappings, and fields

• Documents are docs, JSON objects, etc.
• Indexes - Like a database table. It's a collection of searchable documents
• Mapping - which fields need to be searched for efficiently. You can also specify the data types here for range queries, etc.
• Elasticsearch maps terms (words, numbers) to document IDs

Reverse Indexes

• Features that we want to quickly search for - e.g. Tweets, usernames
• You can use something like CDC - change data capture which can update Elasticsearch whenever content in the db changes

Geospatial indexes