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. I put a lot of thought into it that night and had a fix for it the next morning. As usual, my approach relied on Postgres, and carried a fun lesson.

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.

Say that three times fast! Joking aside, managing database object access is a headache for users and DBAs alike. Postgres isn’t really an exception in that regard, but it does provide a few tools to greatly reduce the pain involved. The crazy thing is that few people even know this feature exists. I’ve known about it for a while myself, but it always slips my mind because it feels so wrong not to explicitly grant permissions.

I recently noted that the COPY command in Postgres doesn’t have syntax to skip columns in source data when importing it into a table. This necessitates using one or more junk columns to capture data we’ll just be throwing away. During that, I completely forgot that friendly devs had contributed alternative file handling methods as Foreign Data Wrappers. Most people think of foreign wrappers as a method for interacting with remote databases. Perusing the full list however, reveals some surprising data sources. Twitter? Hive? Video cards?!