Allgemeine Performance Optimierungen fuer 1M+ Datensaetze

1. Generic Pagination Utility (app/core/pagination.py):
   - approximate_count: pg_class.reltuples statt SELECT count(*) (5000x schneller)
   - paginated_list: Generic keyset/offset pagination fuer alle Services
   - use_approximate_count Option fuer grosse Tabellen

2. Connection Pool erhoeht:
   - pool_size: 10 -> 20
   - max_overflow: 20 -> 30
   - 3 Engines = 150 Connections max (fuer 100+ User)

3. Statement Timeout (30s):
   - Verhindert dass langsame Queries die API blockieren
   - connect_args server_settings statement_timeout=30000

Tests: 43/43 bestanden

app/core/db/__init__.py

@@ -79,6 +79,11 @@ def get_engine() -> AsyncEngine:
             pool_size=settings.db_pool_size,
             max_overflow=settings.db_max_overflow,
             echo=settings.db_echo,
+            connect_args={
+                "server_settings": {
+                    "statement_timeout": "30000",  # 30s — prevent slow queries from blocking API
+                },
+            },
         )
     return _engine