postgres VS rupy

I want to use this as a chance to bring attention to a GitHub issue that I think would help reduce friction for Neon:

https://github.com/neondatabase/neon/issues/4989

If the Neon driver were to allow us to easily pass in a localhost connection, the development and test experience would be easier. Perhaps Neon could swap to something like this internally: https://github.com/porsager/postgres.

Having run a local dev environment connected to Neon and tests connected to Neon got in our way of adoption. We'd prefer to develop and run tests against a regular Postgres localhost database.

To the PMs of Neon, put yourself in the shoes of a new developer thinking of giving Neon a try. What changes will I have to make to my code and my development workflow?

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:

Thanks Pier! Your comment saved me some frustration here :-D

https://github.com/porsager/postgres/discussions/627#discuss...

There's a core client interface here:

- https://www.postgresql.org/docs/current/client-interfaces.ht...

On what makes it postgres.js faster, from author himself:

> it seems Postgres.js is actually faster than, not only pg, but of any driver out-there

- https://github.com/porsager/postgres/discussions/627

- https://porsager.github.io/imdbench/sql.html

When viewed as a DSL for set theory, views, CTEs, set-returning functions, et al are indeed proper first-class query abstractions.

When viewed through the lens of general purpose imperative or functional programming languages, it's easy to see how it can be seen as falling short.

I'll admit much of the tooling and driver APIs leave a lot to be desired.

Some tools do make good efforts though such as nested fragments in this driver.

https://github.com/porsager/postgres#building-queries

I don't think this should turn in to an ORM or not debate, but there are plenty of reasons, especially for the crowd that would do anything to avoid ORMs. Just try to take a peek into the multitude of "ORMs are bad" articles / discussions.

For instance - I would love to be able to use https://github.com/porsager/postgres with sqlite.

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

https://github.com/porsager/postgres

https://github.com/gajus/slonik

They've looked at Postgres.js (https://github.com/porsager/postgres) before — wouldn't mind if they enabled those other cases in the same way.

I have been running a Raspberry 2 cluster for 10 years: http://host.rupy.se

A few weeks back the first SD card to fail got so corrupted it failed to reboot!

My key learning is use oversized cards, because then the bitcycle will wear slower!

I'm going from 32GB to 256/512/1024!

How this article does not mention SSE, comet or chunking escapes me.

What does their definition of event-driven really look like in practice.

Nobody has a clue.

Here is the ideal event driven system, it's async-to-async: https://github.com/tinspin/rupy/wiki/Fuse

The example is not working because I had to shut down the services for multiple reasons, but the high level of it is that you use 4 (potentially different) threads to do one request/response middle man transaction.

That way you have _zero_ io-wait or idling. I'm surprised nobody has copied this approach since I invented it 10 years ago. I understand why though you need your entire chain to be async and that means rewriting everything and that is a big risk when it's hard to debug.

But if you succeed you can build something that is 10x perf/watt than all other implementations. Which is going to be important when interest rates go higher and crash our entire industry.

The hardware is peaking.

So software is where you can make the difference: http://host.rupy.se

I think we're all confused over the definition. Also one might understand what all the proponents are talking about better if they think about this more as a process and not some technological solution:

https://github.com/tinspin/rupy/wiki/Process

All input I have is you want your code to run on many machines, in fact you want it to run the same on all machines you need to deliver and preferably more. Vertically and horizontally at the same time, so your services only call localhost but in many separate places.

This in turn mandates a distributed database. And later you discover it has to be capable of async-to-async = no blocking ever anywhere in the whole solution.

The way I do this is I hot-deploy my applications async. to all servers in the cluster, this is what a cluster node looks like in practice (the name next to Host: is the node): http://host.rupy.se if you click "api & metrics" you'll see the services.

With this not only do you get scalability, but also redundancy and development is maintained at live coding levels.

I have hosted my own web server both physically and codevise since 2014.

It's on a Raspberry 2 cluster:

http://host.rupy.se

Since 2016 i have my own database also coded from scratch:

http://root.rupy.se

We need to implement HTTP/1.1 with less bloat, a C non-blocking web server that can share memory between threads is probably the most interesting project for humans right now, is anyone working on that?

I have one in Java: https://github.com/tinspin/rupy

Here is the 2000 lines of code of the entire database: http://root.rupy.se/code?path=/Root.java

And here you can try it out: http://root.rupy.se

The smallest PaaS you have ever seen is one order of magnitude larger than mine: https://github.com/tinspin/rupy

And I bet you the same goes for performance, if not two!

The data is here: http://fuse.rupy.se/about.html

Under Performance. Per watt the fuse/rupy platform completely crushes all competition because of 2 reasons:

- Event driven protocol design, averages at about 4 messages/player/second (means you cannot do spraying or headshots f.ex. which is another feature in my game design opinion).

- Java's memory model with atomic concurrency which needs a VM and GC (C++ copied that memory model in C++11, but it failed completely because they lack both VM and GC, but that model is still to this day the one C++ uses), you can read more about this here: https://github.com/tinspin/rupy/wiki

You can argue those points are bad arguments, but if you look at performance per watt with some consideration for developer friendlyness, I'm pretty sure in 100 years we will still be coding minimalist JavaSE on the server and vanilla C (compiled with C++ compiler) on the client.