kysely VS MongoDB

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!

How does this compare with my current favorite lite sqlite wrapper kysely? https://kysely.dev/

ORMs suck, but raw SQL embedded in your code sucks too.

This might be good time to plug my TypeScript non-ORM: https://jawj.github.io/zapatos/.

I should say I also like what I've seen of https://kysely.dev/ and https://pgtyped.dev/.

As we can see using Kysely with Nextjs is very simple, and it allows us to create queries in a simple way, create tables, create migrations, transactions, etc.

I've switched to kysely (https://kysely.dev) to just build SQL instead and it's nice to have full SQL access but still be type safe to my schema. Enjoying it so far.

Kysely looks like the thing most people would want. It's not a full ORM though - just a well-typed query builder.

https://kysely.dev/

Kysely

MongoDB

First, visit MongoDB Atlas and create an account, or sign in if you already have one. This article will guide you through the process of creating a MongoDB account. You should be redirected to your dashboard once you have completed the process. Locate the Connect button and click it.

On the other hand, NoSQL databases are non-relational databases. They store data in flexible, JSON-like documents, key-value pairs, or wide-column stores. Examples include MongoDB, Couchbase, and Cassandra.

I built each API with Node.js, Express, and Docker. Services connected to a NoSQL MongoDB database.

In edge computing, managing time series blob data efficiently is critical for performance-sensitive applications. This blog post will compare ReductStore, a specialized time series database for unstructured data, and MongoDB, a widely-used NoSQL database.

MongoDB to store our data as documents, close to JS objects

MongoDB: Known for its ease of development and strong community support, MongoDB is effective in scenarios where flexible schema and rapid iteration are more critical than strict ACID compliance.

MongoDB

Ensure you have MongoDB installed for data storage. You can download MongoDB Community Server from MongoDB's official website or use the cloud cluster.

We will be using MongoDB as a database on both the Auth microservice and notifications microservice, sign up for a MongoDB Atlas account here incase you donot have one and donot have its desktop application(mongodb campass) installed and would like to use mongodb atlas. This cloud-based database service offers a free tier and simplifies the process of managing MongoDB databases.