s4 VS Hasura

the idea of map reduce remains a good one.

there are a number of interesting innovations in streaming systems that followed, mostly around reducing latency, reducing batch size, and alternate failure/retry strategies.

even hadoop could be hard to debug when hitting a performance ceiling for challenging workloads. the streaming systems took this even further, spark being notorious for fiddle with knobs and pray the next job doesn’t fail after a few hours, again.

i played around with the thinnest possible map reduce stack a while back[1][2]. i wanted to understand the performance ceiling for different workloads without all the impenetrable layers of data bureaucracy. turns out modern network and cpu are really fast when you stop adding random software layers like lasagna.

i think the future of data, for serious workloads, is gonna be bespoke. the primitives are just too good now.

1. https://github.com/nathants/s4

2. https://github.com/nathants/bsv

pipes are great. is the other process on another cpu or another machine? honestly who cares.

https://github.com/nathants/s4/blob/master/examples/nyc_taxi...

i dragged my feet on go for a long time. i also thought that skipping go and moving to rust was the play. a few years later, i still write python often, but i don’t build systems with it. python i now use like bash, to glue things together and automate random things. it’s a fantastic language and i will never drop it.

the verbosity of go is the biggest hurdle for a pythonista. the thought of giving up context managers, decorators, iterators, comprehensions, exceptions, coroutines, it’s unthinkable. in comparison go is ugly. your aesthetic mind screams in protest.

write go full time. dive in. as months pass, not only will those aesthetic objections fade, your mental model from python cleanly transforms to go. go is what mypy tried to be. the cost was aesthetic changes. the benefit is worth it.

the zen of python says if it’s easy to explain it might be a good idea. this is go, and it is.

i rebuilt a reasonably sized project from python[1] to go[2] over the last few years. i also have a system that i maintained both python[3] and go[4] implementations for, sharing a test suite in python.

go, like python, is fantastic. use both in whatever amount works for you. don’t read about them, build with them. you won’t regret it.

1. https://github.com/nathants/cli-aws/tree/bb78e529e7d1d3f95ac...

2. https://github.com/nathants/libaws

3. https://github.com/nathants/s4/tree/python

4. https://github.com/nathants/s4

> 2. ORMs do not hide SQL nastiness.

This is certainly true!

I mean: ORMs are now well known to "make the easy queries slightly more easy, while making intermediate queries really hard and complex queries impossible".

I think the are of ORMs is over. It simply did not deliver.

If a book on SQL is --say-- 100 pages, a book on Hibernate is 400 pages. So much to learn just to make the easy queries slightly easier to type? Just not worth it.

I prefer jooq any day over ORMs. And dont get me started over what tools like Hasuna have to offer.

There are also some languages (forgot the names) that are SQL-done-right. Select in the back, more type safe, more logic, more in the same steps as the query gets executed. These need to be adopted by PG and MySQL and we're good to go. (IMHO)

https://www.jooq.org/

https://hasura.io/

[4] https://github.com/hasura/graphql-engine/blob/master/architecture/live-queries.md

Another strategy is to model access control declaratively and enforce it in the application layer. ZenStack (built above Prisma ORM) and Hasura are good examples of this approach. The following code shows how access policies are defined with ZenStack and how a secured CRUD API can be derived automatically.

Today, this ecosystem is going strong with new providers like Hasura, AppWrite and Supabase powering millions of projects. There are a few reasons people choose this style of hosting, especially if they are more comfortable with frontend development. BaaS lets them set up a database in a secure way, expose some business logic on top of the data, and connect via a dev-friendly SDK from their app or website code to save data easily. These modern tools build a blend of managed database with curated plugins such as authentication, great admin dashboards, and function as a service type capability - all in one package, and often offered as a integrated hosted service.

Hi! If you’ve ever thought about something like using GraphQL for something like this.. You might like Hasura. (Obligatory I work for Hasura)

We’ve got an OpenAPI import and you can setup cron-jobs or one-off jobs and do things like load in headers from the environment variables to pass through. There isn’t currently an easy journey for chaining multiple calls together without writing any code at all, but you can wrap pretty much any API endpoint via OpenAPI import or a custom action, and you can even make minor edits to things like the API contract format to change aliases/naming.

Our goal is to join all the things, databases and API’s. Most people know us for instant GraphQL API’s that give you CRUD on your database, but we also wrap APIs.

Not sure if something like this would fit your use-case and do check out some of the other things mentioned, but depending what you are trying to do I think Hasura might potentially work.

You can find out more here: https://hasura.io

Nested Mutation - 113 thumbs up, and still open since 2019... another case of not listening to the users?

Hasura is an open-source real-time GraphQL API server with a strong authorization layer on your database. You can subscribe to database events via webhooks. It can combine multiple API servers into one unified graphQL API. Hasura is a great tool to build any CRUD GraphQL API. Hasura does not have any authentication mechanisms; e.g., you need an auth server to handle sign-up and sign-in.