slonik VS kysely-codegen

And sometimes invest instead in learning a technology rather than hide it: for example slonik encourages you to write normal SQL queries by making SQL templating easier and safer. In turn, your IDE would be able to understand those queries and give you support based on the database schemas you actually have.

I'd push you to consider using postgres, slonik or similar for database queries. With these libraries, you just write SQL, but they perform input sanitization for you. So you can safely write:

You can already use postgres with Slonik.

https://github.com/gajus/slonik#user-content-slonik-how-are-...

It is not going to be the default because it is way slower.

https://github.com/gajus/slonik/actions/runs/6616647651

Test node_version:18 test_only:postgres-integration is taking 3 minutes.

Test node_version:18 test_only:pg-integration is taking 38 seconds.

For those uninitiated, Slonik is a battle-tested SQL query building and execution library for Node.js. Its primary goal is to allow you to write and compose SQL queries in a safe and convenient way. Now, let's see how it pairs with Express.js.

I am the maintainer of Slonik and I am trying to understand what portion of this sub-users are using Slonik vs other libraries, and if they are using anything else – what are their reasons for it.

It's nice that they implemented string templates essentially exactly the same way Javascript template literals and tag functions work. They even give an example of using it to create a prepared statement (e.g. DB."SELECT * FROM foo WHERE bar = \{inputParam}") which is exactly what many NodeJS libraries due, e.g. Slonik https://github.com/gajus/slonik, like sql`SELECT * FROM foo WHERE bar = ${inputParam}`;

I've found libraries like Zod useful when interacting with external data sources like a database. Slonik[1] uses Zod to define the types expected from a SQL query and then performs runtime validation on the data to ensure that the query is yielding the expected type.

I don't think it's necessary to use Zod/runtime validation everywhere, but it's a nice tool to have on hand.

[1]https://github.com/gajus/slonik

Demonstrate how easily and accidentally one can make an SQL injection with these:

https://github.com/porsager/postgres

https://github.com/gajus/slonik

Have you tried Slonik (https://github.com/gajus/slonik)? It won't generate types from queries automatically, but it encourages writing SQL vs. a query builder and allows type annotations of queries with Zod. Query results are validated at runtime to ensure the queries are typed correctly.

Hello HN! I was recently introduced to Kysely (https://github.com/kysely-org/kysely), a type-safe Typescript SQL query builder, and instantly fell in love! I got inspired and wanted to make something similar for AWS DynamoDB.

Thus, I developed Tsynamo! Instead of calling it type-safe, I decided to go with type-friendly, because the library is still in an early stage, and is not 100% type-safe.

Under the hood, Tsynamo compiles the built queries into AWS SDK v3 commands. I feel that Tsynamo simplifies the AWS SDK API quite a lot since the developer doesn't have to mess around with condition/filter expressions or attribute names/values themselves, and as a bonus gets autocompletion for building the queries!

There's also a playground to test it out in your browser: https://try.tsynamo.dev. It might not have the most up-to-date API of the library in use yet, but you can get the library's main idea from there.

Since the project is still in its early stages, it doesn't yet have 100% support for all DynamoDB features, like querying indexes. The next steps will be increasing the support coverage and perhaps adding automatic type generation as inspired by kysely-codegen (https://github.com/RobinBlomberg/kysely-codegen).

Would love to get some feedback, thanks in advance!

Querying the database (PostgreSQL) should not be ground breaking. Personally I like to have full type-safety so we can easily catch bugs during the development time without introducing any tests that are just testing the data type from our datastore to match the data type our API expects. I like to go database schema first, which means that we generate types from the database schema and work with those. Any change to the schema of the database is made with SQL migrations and after that, the typescript types are regenerated. Another approach is to use a code-first tool like TypeORM or Prisma. However in my experience such tools often produce not efficient SQL queries and are less easy to extend. In my projects I use library kysely (https://github.com/koskimas/kysely) with kysely-codegen (https://github.com/RobinBlomberg/kysely-codegen) to have a full type-safe SQL builder.

The main difference to me is that with Prisma I don't need to do any SQL to get a project up and running. I can define the tables and relations from my code or from Prisma Studio, and in one swoop I get the db structure done and the types defined.

I know my way around a database, but I'd rather not leave my code editor whenever I need to add a new column to a table.

With Kysely you have to create the DB schema, and then write the types; with every change you need, you gotta do both again.

(At least this seems true by default; as the project's readme mentions, there is a code generator[1] to generate the types from the DB schema; not quite the same but at least it's better than nothing.)

Commenters say that writing complex queries with Kysely is easier, which makes me wonder if I could use Prisma except for those, since Kysely should be able to just generate the SQL query for me to handle to Prisma...

[1]: https://github.com/RobinBlomberg/kysely-codegen

kysely kysely-codegen kysely-d1 allows access to D1 while using SQL Builder.

For what it's worth, I've been using kysely-codegen to generate the types based on the database schema and it's been working great for me.

I dislike ORMs and have been using Kysely https://github.com/koskimas/kysely and https://github.com/RobinBlomberg/kysely-codegen for a small project and so far I love it. It's a mapper/query builder that is equivalent to Dapper in C# (without the query builder) but with the power of typescript's type system to enforce proper queries. You can also bypass something with the sql to write raw SQL.