sequelts VS FrameworkBenchmarks

You can use these template literal types + infer to build an entire SQL parser. I did a POC that infers SQL query types by parsing the SQL query on a type level:

https://github.com/nikeee/sequelts

However, building this parser is pretty cumbersome and supporting multiple SQL dialects would be lots of pain. While I'm not a fan of query builders per se, Kysely pretty much covers everything that my POC tried to cover (except that 0 runtime overhead). However, you get the option to use different DBMs in tests than in production (pg in prod, sqlite in tests), which is a huge benefit for a lot of people. sequelts was designed to work with sqlite only. And it's not a hack.

The only thing I can imagine where this would be useful is when you don't have control about what DB is being used, for example, when building a product that should be compatible with Postgres and MariaDB (and each is getting used). However, in the age of containerization, this isn't a big problem any more.

In some ORMs, I need to create types that the result of a query containing JOINs is mapped to. Others don't support them _at all_. In TypeORM, there is a query builder which forces you to put in _some_ SQL for things like "WHERE a in (b, c)".

I created a proof of concept of a different approach: Just embrace SQL and provide static typing based on the query. The return type of a query is whatever that thing is that the query returns in the context of the database schema. It's possible to do in TypeScript, by parsing the SQL query at development time:

https://github.com/nikeee/sequelts

One benefit is that it does not need any runtime code, as it's just a type layer over SQL. You don't have to rely on some type-metadata that TypeScript emits. That's why it also works with JavaScript only.

I don't like ORMs that use runtime types either. Most of the time, I want to write raw SQL.

So as an experiment, I created a library that statically types raw SQL:

https://github.com/nikeee/sequelts

The idea is to parse the SQL queries using TS's type system. The parsed query is combined with the database schema and therefore, we know what type the query will return.

This is especially useful due to TS's structural type system.

Neat. Thanks for sharing!

Interestingly, may-minihttp is faring very well in the TechEmpower benchmark [1], for whatever those benchmarks are worth. The code is also surprisingly straightforward [2].

[1] https://www.techempower.com/benchmarks/

[2] https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast...

ntex was formed after a schism in actix-web and Rust safety/unsafety, with ntex allowing more unsafe code for better performance.

ntex is at the top of the TechEmpower benchmarks, although those benchmarks are not apples-to-apples since each uses its own tricks: https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...

Ruby is slow. Very slow. How much you may ask? https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s... fastest Ruby entry is at 272th place. Sure, top entries tend to have questionable benchmark-golfing implementations, but it gives you a good primer on the overhead imposed by Ruby.

It is also not early 00s anymore, when you pick an interpreted language, you are not getting "better productivity and tooling". In fact, most interpreted languages lag behind other major languages significantly in the form of JS/TS, Python and Ruby suffering from different woes when it comes to package management and publishing. I would say only TS/JS manages to stand apart with being tolerable, and Python sometimes too by a virtue of its popularity and the amount of information out there whenever you need to troubleshoot.

If you liked Go but felt it being a too verbose to your liking, give .NET a try. I am advocating for it here on HN mostly for fun but it is, in fact, highly underappreciated, considered unsexy and boring while it's anything but after a complete change of trajectory in the last 3-5 years. It is actually the* stack people secretly want but simply don't know about because it is bundled together with Java in the public perception.

*productive CLI tooling, high performance, works well in a really wide range of workloads from low to high level, by far the best ORM across all languages and back-end framework that is easier to work with than Node.JS while consuming 0.1x resources

Although that seems to have improved in recent years.

https://www.techempower.com/benchmarks/#hw=ph&test=json§...

RoR and whatever C++ based web backend there is count as a valid comparison in my book. But comparing the languages itself is maybe a bit off.

On a side note, you can actually compare their performance here if you’re really curious. But take it with a grain of salt since these are synthetic benchmarks.

https://www.techempower.com/benchmarks

Most benchmarks you'll find essentially have someone's thumb on the scale (intentionally or unintentionally). Most people won't know the different languages well enough to create comparable implementations and if you let different people create the implementations, cheating happens. The TechEmpower benchmarks aren't bad, but many implementations put their thumb on the scale (https://www.techempower.com/benchmarks). For example, a lot of the Go implementations avoid the GC by pre-allocating/reusing structs or allocate arrays knowing how big they need to be in advance (despite that being against the rules). At some point, it becomes "how many features have you turned off." Some Go http routers (like fasthttp and those built off it like Atreugo and Fiber) aren't actually correct and a lot of people in the Go community discourage their use, but they certainly top the benchmarks. Gin and Echo are usually the ones that are well-respected in the Go community.

There is certainly a lot of speculation in Techempower benchmarks and top entries can utilize questionable techniques like simply writing a byte array literal to output stream instead of constructing a response, or (in the past) DB query coalescing to work around inherent limitations of the DB in case of Fortunes or DB quries.

And yet, the fastest Ruby entry is at 274th place while Rails is at 427th.

https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...

oh what machine? with how many workers? doing what?

search for "node" on this page: https://www.techempower.com/benchmarks/#section=data-r21

JustJS would like a word https://www.techempower.com/benchmarks/#section=data-r20&tes...

In terms of RPS, this web service is more-or-less the fortunes benchmark in the techempower benchmarks, once the data hits the cache: https://www.techempower.com/benchmarks/#section=data-r21

Or, at least, they would be after applying optimizations to them.

In short, both of these would serve more rps than you will likely ever need on even the lowest end virtual machines. The underlying API provider will probably cut you off from querying them before you run out of RPS.