A couple of comments as one of the authors of Solr's spatial code:
- I don't think any of us have compared it to PostgreSQL, but I can tell you we have clients doing 500 queries per second+ with it including text search. I've yet to see a DB do good text-based fuzzy matching and combining two systems (DB + search) via a join is usually slow. YMMV.
- The main goal of the implementation is to add point-based search to text search. It is not a general purpose replacement for an r-tree, etc.
- You are not required to use haversine. The distance function is pluggable and we have other options implemented. Also, in many cases, you have other clauses in your query that restrict down the set of documents that need to be scored by distance.
- I don't think any of us have compared it to PostgreSQL, but I can tell you we have clients doing 500 queries per second+ with it including text search. I've yet to see a DB do good text-based fuzzy matching and combining two systems (DB + search) via a join is usually slow. YMMV.
- The main goal of the implementation is to add point-based search to text search. It is not a general purpose replacement for an r-tree, etc.
- You are not required to use haversine. The distance function is pluggable and we have other options implemented. Also, in many cases, you have other clauses in your query that restrict down the set of documents that need to be scored by distance.