Not a lot of people remember what Postgres was like before version 8.4. In many ways, this was the first “modern” release of the database engine. CTEs, Window Functions, column level permissions, in-place upgrade compatible with subsequent versions, collation support, continuous query statistic collection; it was just a smorgasbord of functionality.

There are a smorgasbord of database engines out there. From an outside perspective, Postgres is just another on a steadily growing pile of structured data storage mechanisms. Similarly to programming languages like Rust and Go, it’s the new and shiny database systems like MongoDB that tend to garner the most attention. On the other hand, more established engines like Oracle or MySQL have a vastly larger lead that seems insurmountable. In either case, enthusiasm and support is likely to be better represented in exciting or established installations.

Postgres is great, but it can’t run itself in all cases. Things come up. Queries go awry. Hardware fails, and users leave transactions open for interminable lengths of time. What happens if one of these things occur while the DBA themselves has a hardware fault? While they’re down for maintenance, someone still has to keep an eye on things. For the last PG Phriday of the year completely unrelated to my upcoming surgery, let’s talk about what happens when your DBA becomes inoperative due to medical complications.

Recently a coworker asked me this question:

Should I expect variance between minutes and hours for the same query?

And I was forced to give him this answer:

Potentially, but not commonly. Query planning is an inexact science, and regardless of the query being the “same query,” the data is not the “same data.” This isn’t generally the case, but on occasion, changes in data can affect the query execution path. Usually this is a good thing, as the database accounts for new value distributions.

It’s about the time for year-end performance reviews. While I’m always afraid I’ll narrowly avoid being fired for gross incompetence, that’s not usually how it goes. But that meeting did remind me about a bit of restructuring I plan to impose for 2017 that should vastly improve database availability across our organization. Many of the techniques to accomplish that—while Postgres tools in our case—are not Postgres-specific concepts.