A few days ago, a developer came to me with that inevitable scenario that every DBA secretly dreads: a need for a dynamic table structure. After I’d finished dying inside, I explained the various architectures that could give him what he needed, and then I excused myself to another room so I could weep silently without disturbing my coworkers. But was it really that bad? Databases have come a long way since the Bad Old Days when there were really only two viable approaches to table polymorphism.
In a heterogeneous database environment, it’s not uncommon for object creation and modification to occur haphazardly. Unless permissions are locked down to prevent it, users and applications will create tables, modify views, or otherwise invoke DDL without the DBA’s knowledge. Or perhaps permissions are exceptionally draconian, yet they’ve been circumvented or a superuser account has gone rogue. Maybe we just need to audit database modifications to fulfill oversight obligations. Whatever the reason, Postgres has it covered with event triggers.
Ah, users. They log in, query things, accidentally delete critical data, and drop tables for giggles. Bane or boon, user accounts are a necessary evil in all databases for obvious reasons. And what would any stash of data be if nobody had access? Someone needs to own the objects, at the very least. So how can we be responsible with access vectors while hosting a Postgres database? We already covered automating grants, so let’s progress to the next step: building a “best practice” access stack.
Back in 2005, I started a new job with a company that did work for other businesses. Their data model was designed by developers and they had no DBA, as is pretty common in smaller organizations. A critical part of our main application relied on an event log that captured customer activity and relayed their final decision to the client for reconciliation. One day someone noticed that there was a bug in the system that resolved the final decision from the event stack, and panic ensued.
Sure, managing a Postgres cluster is great. We’ve got the software installed, more tool wrappers than we can wave several sticks at, and a running cluster that’s ready to do our bidding. But what do we do with it? In fact, what is a Postgres cluster anyway? How are databases involved? What about schemas? There’s critically important nomenclature that new users may find somewhat non-intuitive, so let’s demystify things a bit.
