The segments themselves being immutable doesn't mean that Tantivy is incompatible with Postgres - it just means that Tantivy needs to be made compatible with Postgres' concurrency control mechanisms (MVCC) and storage format (block storage). This blog post explains the latter: https://www.paradedb.com/blog/block_storage_part_one
Second - as the article correctly demonstrates, the problem with Postgres FTS isn't "how can I pick and optimize a single pre-defined query" it's "how do I bring Postgres to Elastic-level performance across a wide range of real-world boolean, fuzzy, faceted, relevance-ranked, etc. queries?"
`pg_search` is designed to solve the latter problem, and the benchmarks were made to reflect that. You can always cherry-pick a query and optimize it at the expense of data duplication and complexity. The Neon/ParadeDB benchmarks contained 12 queries in total, and the benchmarks could have:
- Created composite b-tree indexes for each of the queries with boolean predicates
- Extracted the all the text fields from JSONBs, stored and indexed them as a separate columns for queries against JSONB
But that's not realistic for many real-world use cases. `pg_search` doesn't require that - it's a simple index definition that works for a variety of "Elastic style" queries and Postgres types and doesn't ask the user to duplicate every text column.