Can web2py be used for highly complex relational databases for large fiscal projects? Example: California's Fi$cal project - http://www.fiscal.ca.gov/<http://www.linkedin.com/redirect?url=http%3A%2F%2Fwww%2Efiscal%2Eca%2Egov%2F&urlhash=DBJm&_t=tracking_anet> - with roughly 10,000 tables and many complex joins.
What components of web2py would start to get slow or not work well when having so many tables? If web2py would instead be better used to prototype the Fi$cal system, what would be good production-version candidates to migrate to? Pure Python using sqlAlchemy? Java? Anything that would make migration easier such as Python-based frameworks? Thanks, Alex Glaros --
