If the primary search matching criterion is show answer that has three or more of the search terms as tags, then this will be a little tricky to cleanly implement with Postgres.
There are a couple routes you could go, neither of which will execute as fast as an Elasticsearch query:
SQL Subquery on an AnswerTags table:
Something like:
SELECT answer_id
FROM answer_tags
WHERE tag_text IN (<list of query terms>)
GROUP BY answer_id HAVING COUNT(*) >= 3
ORDER BY COUNT(*) desc
Use a Postgres-specific array type to keep all Tags in an Answer field. Write a stored procedure to calculate tag intersection/overlap:
Some suggested approaches in this thread: Postgres - Function to return the intersection of 2 ARRAYs?
If you pursue Elasticsearch as a solution, you'll have much better performance (though if you only have 100 records, this may not be significant), and a more straightforward implementation path. (See the minimum_should_match parameter associated with the match query type).
Elasticsearch also enables a lot more nuance in your matching logic and search features (e.g. tiebreaking cases where multiple records match, autosuggesting answer titles or tags, synonyms/stemming and other text normalization methods)
Elastic recently acquired a great Elasticsearch hosting company Found.no which is a good choice if you want to bypass installation/configuration tasks to get up and running immediately. They offer a 14-day free trial, and Found being owned by Elastic, upgrades faster than any other ES hosts and includes premium plugins with each cluster instance.
