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Comment by steffres | Hacker News Reader

That sounds reasonable. But what about the case where the DB migration of version 2 would be incompatbile with code version 1, e.g. a column was dropped?

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You NEVER do that in one go, you need to split it in several deployments. Dropping a column is relatively straightforward, in two steps. First deploy a version of the code that doesn’t use the column, then release the migration dropping the column.

The typical example is the renaming of a column, which needs to be done in several steps:

1. Create the new column, copying the data from the old column (DB migration) both columns exist, but only the old one is used

2. Deploy new code that works with both columns, reading from old and writing new and old

3. Deploy data migration (DB migration) that ensures old and new columns has the same values (to ensure data consistency). At this point, there are no “old column only” writes by the code deployed in previous step

4. Deploy new code using only new column. Old column is deprecated

5. Delete old column

At any given point, code versions N (current) and N-1 (previous) are compatible with the DB. Any change on the DB is done in advance in a backwards compatible way.

I see. Thanks for the clarifications.

And these DB migrations, did your team keep a history of them? If so, did you manage them yourselves, or did you use some tools like flyway?

I'm asking because I'm starting a project where we will manage the persistence SQL layer without any ORM (always did it so far with Django's migrations), but might consider some third party tools for DB migrations.

btw. it's also bad to drop a column if you have multiple people in a team when they switch between branches. it's always a headache, so the best thing is to delay dropping/deleting.

renaming stuff with that gets a little bit tricky, but you can workaround that with database triggers if you really need to rename things.

The problem I've seen a lot, particularly with Rails, is when migrations generate a schema dump after running them, which can get really messy if people blindly commit the diff or if you rely on running several years of migrations in your local environment from scratch (many of which may have been edited or removed if they directly referenced application code). Given the migrations are executed through a DSL and the dump is just a structural snapshot of the DB at the end of the run, they're not quite as reproducible as plain SQL migrations.

You just end up with weird, unpredictable DB states that don't reflect production at all. Especially when you're dealing with old versions of MySQL and the character encoding and collation are all over the place.

The way I've seen it work is hand written SQL for the migrations, numbered and tracked in Git.

There shouldn't be any reason that you can't do it with Flyway, but I would be concerned about fighting Flyway a bit. I use Django a fair bit and I honestly don't see a good way to make this approach work for Django, not suggesting that you can't, but you would be fighting Django a fair bit, it's not really how it's designed to work.

If you don't have en ORM, then this is actually much much easier to do right. I'd design the initial schema, either by hand or using some pgAdmin, TOAD or whatever you database has. For there on everything is just hand written migrations.

Django has migrations; why would this be harder with Django?

The migrations is fairly tightly couple to the code. You can apply the migrations without deploying new code, if you extract the migrations, but now you have at least two branches in your version control, both of which are technically in production. You have the version that's actually running, and you have the version with the model changes and the migrations, from which you extracted the migrations and applied to the database.

I'd argue that because you're making the migrations from the model, it's also easier to do accidentally create migrations that are not independent of the code version.

Hm, but isn't that right? You make your change in code, which doesn't touch your models (except you're no longer using the column you'd like to deprecate), and deploy that; show it's working. Then you make another change to actually remove the column from the models and generate a migration. Then you deploy that version, which migrates the db and runs your new model code?

(You could in theory remove the column but not merge the migration if you wanted to show your code worked fully without that column in your ORM model before removing it from the DB as well?)

Django migrations have painful edge cases when you deal with data migrations.

I didn't mean to use Django _and_ a separate migration tool. It's just that I did work with Django so far, but switching now to a new codebase without it. Hence my question for experiences in DB migration.

At work we use Django migrations. It helps. But the core of schema evolution is backward compatibility. To reach this goal, code review is necessary.

Here we never drop columns, only add new colunms, also never change column types.

When it comes to constraints (not null or something else) we double check about backwards compatibility.

Changing data is not a robust rollback.

You can also check out Bytebase, it's GitLab for database schema migrations (Disclaimer: I am one of the authors)

We've used dbmate[1] outside of the Django/alembic ecosystem.

[1] https://github.com/amacneil/dbmate

What about new rows added during step 0 - 2

You do it in two stages. Add as new column, deploy code that uses it and no longer use the old column. Then later drop the column once nothing is using it anymore.

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