Sure, this problem can be solved as can any other -- but there's a cost to it in development time. For every feature, the dev working on it had to do it in 3 steps to ensure backwards compatibility and handle partial migration failures gracefully. Imagine doing this for a small feature - the ops effort dwarfs the actual feature! Many small features would probably be dropped.
Multi-single-tenant actually makes it easier to do transactional schema upgrades because these operations only impact one customer at a time. No fiddling with middle-of-the-migration state.
It becomes a non-issue if you're able to go down for a few moments.
Not necessarily viable for some software though, it just depends on what you're running.
(Especially because you can apply the migration on slave and subsequently switch master, making this downtime as quick as the time your system needs to do a database switch.)
This doesn't apply to big services with millions of users, however.
> You roll the feature out incrementally to the users who are ready. You build backwards compatible features. Basic software engineering.
The parent mentioned having to support ~150 B2B customers, so the effort is amplified x100 — more than 100 individual customers databases have to be coddled as you’ve described, albeit they are stuck with poor tooling to manage changes across their unusual architecture.
While not a web-app, we too have ~200 B2B customers running our application and each one have their own DB. Some self-host, most others are hosted by us.
We have written our own tool to upgrade the DB schema, it's nothing fancy, just takes an XML description, compares with the current DB and makes changes. However it ensures the upgrade process is automated.
New versions of our application come with a new DB schema, and we also have an auto-updater for our software. We have a small launcher application which allows the users to select a few older versions of our software, so upgrades are almost always safe in the sense that if the user encounters a bug with the new version, they can try in the previous one.
If the DB schema upgrade tool fails for some reason, the application upgrade will be held back and we'll get a notification.
Combined this allows us to be quite aggressive with pushing out new versions, and to do so without manual intervention.
A limitation with this setup is that DB changes have to be backwards compatible. So we do have a few cases of "if this table exists do this, else do that" type logic and similar, but mostly it's not a big deal.
For example I recently had to refactor some old table where they had used five columns for some additional references (ref_1, ref_2 etc), into a new table of additional references. To handle this I just made a new view which would return either the refs from the new table, or the data from the columns in case the new table didn't have any data for that record.
I then changed the application to use a grid instead of five separate edit controls, and to use this new view. If the user had to use an older version, that version would just write to the five fields and not populate a row in the new table, and the view would then return this data if the user later viewed it in the new version of our application.
So the "overhead" of backwards compatibility in this case was just ensuring this would be sufficient and writing that view, so just a few minutes.
Doing the same thing to 100 databases is usually easy to automate.
I managed a group that had a dozen customers on a single multi-tenant database and some migrations took more than a day - we needed to set maintenance windows on weekends (and once we had to roll back after an error).
Having a dozen databases we could roll out updates to on a client per client basis would have saved us from some enormous headaches.