Also:
> Squeezing the query language into some sql-like shape will provide marginal gain at best.
... is disingenuous at best. In both examples I raised (and in the ones you'll find if you query the others) the engines have functionality to accept user input pretty much as is - meaning as your typical mom would type it in a search field.
If you need extra criteria from there and the dialect's full text syntactic features, you can use regular SQL conditions (and joins, and aggregates, etc.) on the subset of records found. The most discriminating criteria/index will be the one related to the search query in most cases. And when not, lucky you - your query planner did not hammer everything with the same sledgehammer, thus demonstrating why you should be using SQL.
What I see at your zombodb link is just a way to make Postgres proxy requests to ES - complete with ES syntax and/or Query DSL. The only difference is that instead of connecting to ES directly you connect to Postgres and then add "SELECT" thing in front of your ES Query DSL. If it makes something easier, fine, but it's not "Postgres full text over ES".
Think of it as browser prefixes. Sooner or later all engines agree on a common syntax, with each one needing to support some legacy code.
And in contrast with what happens when you use some third party app, you can further filter matched rows, join them with other tables to your heart's contents, aggregate them, apply window functions, and what have you.
There are much better options than LIKE and regexes in SQL for text search. To mention but two:
https://www.postgresql.org/docs/current/static/textsearch-in... https://dev.mysql.com/doc/refman/8.0/en/fulltext-natural-lan...All main engines support full text search in one way or another. TSQL, Oracle, DB2... even SQLite.
What more, these engines all support inverted tree indexes in one form or another - i.e. the same type of index Lucene uses - to make this efficient. This is completely different from the typical LIKE or regex query against a column with a BTree index.