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Show HN: A Full-Stack Web Framework Written in Go
18 projects | news.ycombinator.com | 13 May 2022
Thanks for your comment and question @onionisfruit. Top-notch handle too!
>> What are your plans for models and persistence?
1. High-level, type-safe "ORM" that's generated from your database schema.
GUI to modify data in CloudSQL tables
1 project | reddit.com/r/googlecloud | 9 May 2022
Something like that? https://github.com/xo/xo
We Went All in on Sqlc/Pgx for Postgres and Go
31 projects | news.ycombinator.com | 8 Sep 2021
I'm a big fan of the database first code generator approach to talking to an SQL database, so much so that I wrote pggen (not to be confused with pggen, as far as I can tell a sqlc fork, which I just recently learned about).
I'm a really big partisan of this approach, but I think I'd like to play the devil's advocate here and lay out some of the weaknesses of both a database first approach in general and sqlc in particular.
All database first approaches struggle with SQL metaprogramming when compared with a query builder library or an ORM. For the most part, this isn't an issue. Just writing SQL and using parameters correctly can get you very far, but there are a few times when you really need it. In particular, faceted search and pagination are both most naturally expressed via runtime metaprogramming of the SQL queries that you want to execute.
Another drawback is poor support from the database for this kind of approach. I only really know how postgres does here, and I'm not sure how well other databases expose their queries. When writing one of these tools you have to resort to tricks like creating temporary views in order infer the argument and return types of a query. This is mostly opaque to the user, but results in weird stuff bubbling up to the API like the tool not being able to infer nullability of arguments and return values well and not being able to support stuff like RETURNING in statements. sqlc is pretty brilliant because it works around this by reimplementing the whole parser and type checker for postgres in go, which is awesome, but also a lot of work to maintain and potentially subtlety wrong.
A minor drawback is that you have to retrain your users to write `x = ANY($1)` instead of `x IN ?`. Most ORMs and query builders seem to lean on their metaprogramming abilities to auto-convert array arguments in the host language into tuples. This is terrible and makes it really annoying when you want to actually pass an array into a query with an ORM/query builder, but it's the convention that everyone is used to.
There are some other issues that most of these tools seem to get wrong, but are not impossible in principle to deal with for a database first code generator. The biggest one is correct handling of migrations. Most of these tools, sqlc included, spit out the straight line "obvious" go code that most people would write to scan some data out of a db. They make a struct, then pass each of the field into Scan by reference to get filled in. This works great until you have a query like `SELECT * FROM foos WHERE field = $1` and then run `ALTER TABLE foos ADD COLUMN new_field text`. Now the deployed server is broken and you need to redeploy really fast as soon as you've run migrations. opendoor/pggen handles this, but I'm not aware of other database first code generators that do (though I could definitely have missed one).31 projects | news.ycombinator.com | 8 Sep 2021
I've used https://github.com/xo/xo, extended it with some custom functions for templating, extended the templates themselves, and can now generate CRUD for anything in the database, functions for common select queries based on the indices that exist in the database, field filtering and scanning, updates for subsets of fields including some atomic operations, etc. The sky is the limit honestly. It has allowed me to start with something approximating a statically generated ORM and extend it with any features I want as time goes on. I also write .extra.go files along side the generated .xo.go files to extend the structs that are generated with custom logic and methods to convert data into response formats.
I like the approach of starting with the database schema and generating code to reflect that. I define my schema in sql files and handle database migrations using https://github.com/golang-migrate/migrate.
If you take this approach, you can mostly avoid exposing details about the SQL driver being used, and since the driver is mostly used by a few templates, swapping drivers doesn't take much effort.
sqlh - The SQL Helper
3 projects | reddit.com/r/golang | 3 Jun 2021
Here is an example of the MySQL Django tables generated by GORM https://github.com/xo/xo/tree/master/examples/django/mysql
Fighting boilerplate with code generation
3 projects | dev.to | 10 Apr 2021
10 projects | reddit.com/r/golang | 10 Apr 2021
Implicit In-order Forests: Zooming a billion trace events at 60fps
3 projects | news.ycombinator.com | 30 Apr 2021
Check out http://btrdb.io/ which is a similar idea. It's a distributed database as well. It was designed for storing billions or even trillions of records for electrical data from hundreds of sources at once.
It was written by a couple of friends of mine and others, so I'm not sure how it compares to the article link, as I'm not a databases expert.
What are some alternatives?
sqlc - Generate type-safe code from SQL
InfluxDB - Scalable datastore for metrics, events, and real-time analytics
prometheus - The Prometheus monitoring system and time series database.
igor - igor is an abstraction layer for PostgreSQL with a gorm like syntax.
SQLBoiler - Generate a Go ORM tailored to your database schema.
jet - Type safe SQL builder with code generation and automatic query result data mapping
sql-migrate - SQL schema migration tool for Go.
Squirrel - Fluent SQL generation for golang
go-mysql - a powerful mysql toolset with Go
goleveldb - LevelDB key/value database in Go.
tempdb - Key-value store for temporary items :memo: