planetscale-java VS zod

For MySQL, we've got PlanetScale, and for PostgreSQL, there's Neon.

PlanetScale – database

PlanetScale and Ghost were previously incompatible due to differences in their support for foreign key constraints. With PlanetScale now supporting foreign key constraints, a seamless collaboration between the two is achievable. Nonetheless, there remain minor incompatibilities that require resolution.

PlanetScale: The MySQL database ensuring data integrity and performance.

AWS Serverless MySQL/Postgres offerings are straight trash. I used v1 to build a new app but had nothing but problems. Extremely slow starts (from zero), horrible scaling (it would always get stuck), (relatively) huge bills for the smallest capacity, limitations all over the place. After the first year on that I looked into v2 but my costs would have doubled and I didn't believe their promises of faster scaling. I moved to PlanetScale [0] and was very happy ($30/mo covered prod and dev/qa vs well over that for v1 even with having scale to zero on the AWS dev/qa instances). Also you can quickly be forced into paying for RDS Proxy if you are using lambdas/similar which is not cheap (for me). PS doesn't scale to 0 but at the time $30/mo was a decent savings over AWS Aurora Serverless.

This year I started to run into some issue with PS mainly around their plans changing (went from pay for reads/writes/storage to pay for compute/storage). Yes, yes, I know they still offer the $30/mo plan but it's billed as "Read/write-based billing for lower-traffic applications" and they dropped all mentions of auto-scaling. That coupled with them sleeping your non-prod DB branches (no auto-wakeup, you had to use the API or console) even after saying that was a feature of the original $30 plan rubbed me the wrong way. Eventually the costs (for what I was getting) were way too out of whack. My app is single-tenant (love it or hate it, it's what it is) so for each customer I was paying $30/mo even though this is event-based software (like in-person, physical events that happen once a year) so for most the year the DB sat there and did nothing.

Given all that I looked into Neon [1] (which I had heard of here on HN, but PS support suggested them, kudos to them for recommending a competitor, I always liked their support/staff) and while going from MySQL to Postgres wasn't painless it was way easier than I had anticipated. It was one of the few times Prisma "just worked", I don't think I'd use it again though, that DB engine is so heavy especially in a lambda. I just switched over fully last week to Neon and things seem to have gone smoothly. I can now run multiple databases on the same shared compute and it scales to 0. In fact it's scale up time is absurdly fast, the DB will "wake up" on it's own when you connect to it and unlike AWS Aurora Serverless v1 it comes up in seconds instead of 30-60+ so you don't even have to account for it. With AWS I had to have something poll the backend waiting to see if the DB was awake yet, to fire off my requests, if it was asleep. With Neon I don't even consider it, the first requests just take an extra second or two if that.

I don't have any ill will towards PlanetScale and I quite enjoyed their product for almost the whole time I used it. Also their support is very responsive and I loved the branching/merging features (I'll miss those but zero-downtime migrations aren't required for my use-case, just nice to have). In fact if I had written my app to be multi-tenant then I'd probably still be on them since I could just scale up to one of their higher plans. It does seem like Neon is significantly (for me/my workload) cheaper for more compute, I had queries taking _forever_ on PS that come back in a second or less on Neon all while paying less.

All that said, I _highly_ recommend checking out Neon if you need "serverless" hosting for Postgres that scales to 0.

[0] https://planetscale.com/

[1] https://neon.tech/

See dashboard here

Planetscale: https://planetscale.com/ has a free plan with 5GB storage and limit on reads/writes

[Zod Documentation](https://zod.dev/) [Zod Error Handling](https://zod.dev/ERROR_HANDLING?id=error-handling-in-zod) [React-Hook-Form Documentation](https://react-hook-form.com/get-started) [Hookform Resolvers](https://www.npmjs.com/package/@hookform/resolvers)

This is a very fair comment, and you seem open to understanding why types are useful.

"problems that are due to typing" is a very difficult thing to unpack because types can mean _so_ many things.

Static types are absolutely useless (and, really, a net negative) if you're not using them well.

Types don't help if you don't spend the time modeling with the type system. You can use the type system to your advantage to prevent invalid states from being represented _at all_.

As an example, consider a music player that keeps track of the current song and the current position in the song.

If you model this naively you might do something like: https://gist.github.com/shepherdjerred/d0f57c99bfd69cf9eada4...

In the example above you _are_ using types. It might not be obvious that some of these issues can be solved with stronger types, that is, you might say that "You rarely see problems that are due to typing".

Here's an example where the type system can give you a lot more safety: https://gist.github.com/shepherdjerred/0976bc9d86f0a19a75757...

You'll notice that this kind of safety is pretty limited. If you're going to write a music app, you'll probably need API calls, local storage, URL routes, etc.

TypeScript's typechecking ends at the "boundaries" of the type system, e.g. it cannot automatically typecheck your fetch or localStorage calls return the correct types. If you're casting, you're bypassing the type systems and making it worthless. Runtime type checking libraries like Zod [0] can take care of this for you and are able to typecheck at the boundaries of your app so that the type system can work _extremely_ well.

[0]: https://zod.dev/ note: I mentioned Zod because I like it. There are _many_ similar libraries.

Zod is an open-source schema declaration and validation library that emphasizes TypeScript. It can refer to any data type, from simple to complex. Zod eliminates duplicative type declarations by inferring static TypeScript types and allows easy composition of complex data structures from simpler ones. It has no dependencies, is compatible with Node.js and modern browsers, and has a concise, chainable interface. Zod is lightweight (8kb when zipped), immutable, with methods returning new instances. It encourages parsing over validation and is not limited to TypeScript but works well with JavaScript as well.

Zod is a TypeScript-first schema declaration and validation library. It helps create schemas for any data type and is very developer-friendly. Zod has the functional approach of "parse, don't validate." It supports coercion in all primitive types.

Link: https://zod.dev/

You can check out their documentation here.

You can learn more about Zod on their website here.

In JS, it's a good idea anyway to use some JSON parsing library instead of JSON.parse.

With Zod, you can use z.bigint() parser. If you take the "parse any JSON" snippet https://zod.dev/?id=json-type and change z.number() to z.bigint(), it should do what you are looking for.

We will validate our input using client-side zod. Zod handles TypeScript-first schema validation with static type inference. This means that it will not only validate your fields, it will also set types on validated fields.