A system that ran beautifully in year one can slow down for reasons that have nothing to do with how it was built. It's simply been collecting years of history nobody went back to deal with.
This shows up in ordinary ways. Reports that used to run in seconds start taking minutes. Backups that took twenty minutes start taking hours. A dashboard that felt instant starts to lag. None of this is a single dramatic failure. It arrives slowly enough that nobody notices the exact moment it became a problem.
Part of the cause is simply data nobody has looked at in years: old notifications, historical logs, records kept "just in case" that quietly became permanent. None of that is wrong to keep, if there's a real reason. But treating five year old data with the same priority as this morning's transactions is what makes everything else slower than it needs to be.
There's a technical wrinkle behind this that I think gets missed. Most databases don't fully delete an old version of a record the instant it's updated. They keep it around briefly in case another process still needs it, and a cleanup step is supposed to reclaim that space afterward. In a healthy system this happens quietly in the background. In a neglected one, that cleanup falls behind, and a table showing 20 million active rows can be physically carrying several times that in leftover space nobody's collecting. I've walked into systems where the row count looked completely reasonable and the actual storage told a very different story.
The database is also constantly making guesses about your data's shape to decide how to answer queries efficiently, based on a snapshot it took at some point in the past. If a table used to be evenly spread across customers and now 95% of the rows belong to a handful of large accounts, and nobody's told the database that, it can keep planning around an assumption that stopped being true months ago. I'd call this a maintenance problem rather than a bug, and it's genuinely invisible until someone checks for it specifically.
The other part of the cause is maintenance most companies never schedule, because nothing is technically broken yet. Indexes built to find data quickly need periodic review as usage patterns change, or they start costing more than they save. And backups are the thing everyone assumes works until the day they actually need one. I care about backups existing. I care a lot more about whether anyone has actually restored one recently, because a backup nobody has tested isn't a safety net, it's an assumption.
None of this requires a rebuild or a migration. What it needs is someone treating database maintenance as a real, scheduled piece of work rather than something that only gets attention during an incident.
Ask your team: When did we last restore a backup to check it actually works, and when did we last review which indexes we're maintaining that nobody uses anymore?
If neither has a recent, confident answer, it's worth a half day of engineering time now. The alternative is finding out during an outage, which is a much more expensive way to learn the same thing.