gh-ost VS Prisma

I’ve been through multiple incidents where everything worked fine in the testing environment but ended up locking the production database for minutes when deployed. A category of open-source tools called OSC (Online Schema Change) exists to mitigate such pain, like gh-ost used by GitHub and OSC used by Meta. They work by creating a set of "ghost tables" to apply the migrations, copy over old data from the original tables, and catch up with new writes simultaneously. When all old data is migrated, you can trigger a cutover to make the "ghost tables" production. Check the post below for a great introduction and comparison:

Sounds like it's basically explained in the gh-ost readme https://github.com/github/gh-ost#how

I think it amounts to "use views to decouple access to the table with a fixed interface" and "use triggers for migrating data between tables"

Gh-ost is the new hotness. Simple to use and lots of great features: https://github.com/github/gh-ost

If the performance of the db is a concern during migrations (locking, high cpu consumption for large writes) there are tools that can help and do similiar to what your describing but with the benefit that they are battle tested tools. This one spring to mind https://github.com/github/gh-ost there are other options as well and its worth reading the trade off docs

Not sure which version of MySQL you're using, but one approach would be to use a tool like pt-online-schema-change (from Percona) or g-host -- which will create a duplicate table and then swap it in place of the original table. It's a safer approach when operating in production environments. Here's a good comparison of the tools many people use https://planetscale.com/docs/learn/online-schema-change-tools-comparison

No, especially on large tables with billions of records. They make online schema changes impossible. More details: https://github.com/github/gh-ost/issues/331#issuecomment-266...

Tip #4: Consider slow-running migrations. Some tables can be so large that the traditional migration way is simply not a viable option for them. In such cases, you can consider embedding the data migration code right into your application, or use a special utility like GitHub's online schema migration for MySQL. A slow-running migration can work in production for days or even weeks. It gradually converts the data by small chunks, so you can carefully balance the load on the database while making sure that it doesn't cause slowness or downtime.

GitHub gh-ost

Actually I never tried but I was scared by the small print of GH not using RDS themselves [1] and Ghost relying on lower-level features that might be not easily available in RDS. Also I had the impression you have to setup a normal non-RDS replica attached to your RDS master?

[1] https://github.com/github/gh-ost/blob/master/doc/rds.md

In the world of software development, there are two kinds of developers: those who have never had to complain about ORMs and those who have actually used them. Whether it’s Django ORM for Python, Active Record for Ruby, GORM for Golang, Doctrine for PHP, or Prisma for TypeScript, a common issue persists: writing simple queries is straightforward, but constructing complex or optimized queries can take hours, if not days.

Support for a Union type #2505

generator client { provider = "prisma-client-js" binaryTargets = ["native", "rhel-openssl-1.0.x"] } datasource db { provider = "postgresql" // NOTE: When using mysql or sqlserver, uncomment the @db.Text annotations in model Account below // Further reading: // https://next-auth.js.org/adapters/prisma#create-the-prisma-schema // https://www.prisma.io/docs/reference/api-reference/prisma-schema-reference#string url = env("DATABASE_URL") } model Post { id Int @id @default(autoincrement()) name String createdAt DateTime @default(now()) updatedAt DateTime @updatedAt createdBy User @relation(fields: [createdById], references: [id]) createdById String @@index([name]) } // ... rest of the schema

Unfortunately Prisma hasn’t supported polymorphism yet. As such, you can't use inheritance to model the entity in the same way as in your programming language, as depicted in the above class diagram. The good news is that we could intimate it using table inheritance to imitate it.

In this project I am manually declaring the data types. For better type-safety, use Prisma, which automatically generates types based on your database schema.

When you're creating a full-stack application, you'll also need to write logic to interact with your database. For relational databases like Postgres, you can do this with SQL, or an ORM like Prisma.

Prisma is a modern TypeScript-first ORM that allows you to manage database schemas easily, make queries and mutations with great flexibility, and ensure excellent type safety.

Prisma

There have been multiple feature requests to add native support for AsyncLocalStorage to Prisma, but they haven't been met with much enthusiasm from the maintainers. Some people solved it by extending and overriding the client (which is arguably prone to breaking with updates).