It can't go that far. Postgres is limited by dictionaries, stemming/processing, query semantics (like fuzzy searching), and the biggest issue of all being a lac

It can't go that far. Postgres is limited by dictionaries, stemming/processing, query semantics (like fuzzy searching), and the biggest issue of all being a lack of modern relevance algorithms. It's good for limited scenarios where you just need more than a SQL LIKE statement, and chaining some functions together can get you decent results [1] without adding another datastore. However search tech is pretty mature with Lucene at the core and there are many better options [2] from in-process libraries to simple standalone servers to full distributed systems like Elastic. There are also other databases (relational like MemSQL, or documentstores like MongoDB/RavenDB) that are adding search as native querying functions with most of the abilities of ES. If search is a core or complex part of your application (like patterns in raw image data or similarities in audio waveforms) then that's where ES will excel. 1. https://stackoverflow.com/questions/46122175/fulltext-search-combined-with-fuzzysearch-in-postgresql/51433877#51433877 https://stackoverflow.com/questions/46122175/fulltext-search... 2. https://gist.github.com/manigandham/58320ddb24fed654b57b4ba22aceae25 https://gist.github.com/manigandham/58320ddb24fed654b57b4ba2...