For many data aficionados, Postgres is the way to store and manage relational data. It’s efficient, it’s straightforward, and it plays nice with other tools. But even Postgres has its limits. When you’re working with a relentless stream of live data, you may catch Postgres chugging along on the struggle bus: slower queries, more maintenance requirements, and enough database upkeep to make your autovacuum beg for a pit stop. Developers are increasingly turning to Postgres as a foundation for AI applications, thanks in part to its flexibility and extensive ecosystem. But you might hit its...

Source: The New Stack