RDBMS do query optimization by trying out different plans and picking the best via cost estimations. With prepared statements you can reuse that optimization so

RDBMS do query optimization by trying out different plans and picking the best via cost estimations. With prepared statements you can reuse that optimization so the cost is (kinda) amortized. If you want something deeper you'd need an optimizing sql compiler. The closest I know is DSH (database supported haskell) which translates haskell comprehensions into reaonably optimized sql. The name is a nod to data parallel haskell which used the same flattening transformation for automatic parallelization of comprehensions. https://db.inf.uni-tuebingen.de/staticfiles/publications/the-flatter-the-better.pdf https://db.inf.uni-tuebingen.de/staticfiles/publications/the... Though this system can't come up with answers like 'add an index', 'split this table' or 'add sharding' so for the complex cases it doesn't really help.