I'd argue that relevancy is more your application application's design then the underlying system retrieving the results. For example, putting the same dataset in Postgres or ES wouldn't make one deliver more relevant results given equal configurations.
You could lean on the relevancy strategies built in to ES, but in my experience you're better off understanding what relevancy means for your dataset and implementing a strategy yourself. Your millage may vary though, I'd never advocate reimplenting something that's already provided by your chosen tool.
The options and tools for configuring and tweaking relevancy between ES and PostgreSQL's FTS are surprisingly similar for many application use cases. If you're interested you can check out Postgres' search rank and query weighting configurations.
You could lean on the relevancy strategies built in to ES, but in my experience you're better off understanding what relevancy means for your dataset and implementing a strategy yourself. Your millage may vary though, I'd never advocate reimplenting something that's already provided by your chosen tool.
The options and tools for configuring and tweaking relevancy between ES and PostgreSQL's FTS are surprisingly similar for many application use cases. If you're interested you can check out Postgres' search rank and query weighting configurations.