TypeORM VS PostgreSQL

If you use Sequalize, TypeORM or for MongoDB, we have Mongoose these types of ORM tools, then you are safe by default because these help us against the SQL query injection attacks by default.

We decided to use MySQL for a database. and TypeOrm for ORM. The ER diagram is provided below. For example, the task_assignments table holds information about user assignments to tasks. While in DDD, there is a pattern to design denormalized tables that reflect the structure of domain objects more directly, but this time, a more conventional table design was chosen. TypeOrm models:

How does this compare to using directly an ORM lib that supports browser like TypeORM [0] via SQL.js [1]?

[0] https://typeorm.io/

* Patch a third-party library that was setting an HTTP header to `null`. NodeJS handles this case just fine, but Deno throws an error [2].

After all of that work, I finally was able to use Deno in my project. It was really cool! Unfortunately, both VS Code and IntelliJ with Deno are essentially unusable [3]. Or, at least, unacceptably slow compared to what I had with NodeJS.

[0]: https://stackoverflow.com/a/66073607

[1]: https://github.com/typeorm/typeorm/issues/6123#issuecomment-...

[2]: https://github.com/Sansossio/twisted/issues/97

[3]: https://github.com/denoland/vscode_deno/issues/895

TypeORM is a very convenient ORM for JS apps. We use it with NestJS and running it on NodeJS.

We are going to start using TypeORM as an ORM to help us interact with Postgres, but we also have an example of using Prisma in the future and everything that we have to adapt to switch the ORMs if necessary. At the end we are implementing neon.tech as a production database, right? 😉

TypeORM is a popular Object-Relational Mapping (ORM) library for Node.js. It provides a high-level abstraction over relational databases, making it easy to perform CRUD (Create, Read, Update, Delete) operations.

TypeORM places its focus on TypeScript and JavaScript (ES7+) development. It offers compatibility with various database systems, including MySQL, PostgreSQL, SQLite, and MongoDB. What sets TypeORM apart is its robust integration with TypeScript. It provides a user-friendly experience with a convenient decorator-based syntax for defining entities and relationships. Additionally, TypeORM supports the repository pattern and enables eager loading, enhancing its versatility for developers.

ᴬ typeorm officially supports mssql@v9, but the support for the custom stream builder was added in mssql@v10. Since mssql is a peer dependency of typeorm, you can force override it and use the Cloud SQL Connector with typeorm. There is an open PR to add support for mssql@v10 in typeorm.

pg doesn't do too well with serverless, dead connections are left in the pool (or something)

https://github.com/brianc/node-postgres/issues/2112

If you don't want to use ORM then there are some other packages as well! For PostgreSQL we have node-postgres

Interface with PostgreSQL database

(Instead of the following with pg.)

So far every JS framework that uses https://node-postgres.com works great and so no reason to think Drizzle wouldn't.

One thing that keeps coming up is that SQL equals low productivity. I don't think this is true. I think the culprit is that most developers are using to heavily abstracting SQL using ORMs like Prisma that hides the database and SQL logic.

Since building a SQL generator (https://aihelperbot.com) as a side project, I have become much more proficient in SQL and even though I am also locked into Prisma, I use the `queryRaw` all the time to execute raw SQL queries. You can understand the code without knowing Prisma API. It is more performant. For more complex SQL queries, I use the SQL generator for initial suggestions and adapt if needed.

For the next projects I build I want to use the minimal Postgres client (https://github.com/brianc/node-postgres) combined with a lightweight migration library.

For newer projects I use the small Postgres client. Initially my leap into SQL was lead by AI but as I refreshed and relearned SQL, I now use a mixture of AI and self-written SQL queries. Something like this is just easier to have AI do the grunt work and then adjustment as needed.

This was a known issue for pg developers, and they managed to fix it a long time ago (at the pg level), but the knowledge of this problem didn't reach Knex maintainers.

Integrate the database into your application itself with a postgres client library allowing your applications to make infrastructure changes (like provisioning sharded resources for a client that wants isolation, or using a more accurate forecasting model to pre-allocate more resources before the storm hits).

node-postgres (raw sql, without ORM)