marmot VS sqlc

If you're willing to accept eventual consistency (a big ask, but acceptable in some scenarios) then there are options like marmot [1] that replicate cdc over nats.

[1]: https://github.com/maxpert/marmot

I've written a whole SQLite replication system that works on top of RAFT ( https://github.com/maxpert/marmot ). Best part is RAFT has a well understood and strong library ecosystem as well. I started of with libraries and when I noticed I am reimplementing distributed streams, I just took off the shelf implementation (https://docs.nats.io/nats-concepts/jetstream) and embedded it in system. I love the simplicity and reasoning that comes with RAFT. However I am playing with epaxos these days (https://www.cs.cmu.edu/~dga/papers/epaxos-sosp2013.pdf), because then I can truly decentralize the implementation for truly masterless implementation. Right now I've added sharding mechanism on various streams so that in high load cases masters can be distributed across nodes too.

Very interesting! I have question ( out of my experience in https://github.com/maxpert/marmot ) how do get around the boot time, specially when a change log of table is pretty large in Postgres? I've implemented snapshotting mechanism in Marmot as part of quickly getting up to speed. At some level I wonder if we can just feed this PG replication log into NATS cluster and Marmot can just replicate it across the board.

One of the reasons I started writing Marmot (https://maxpert.github.io/marmot/) was for replicating bunch of tables across regions that were read heavy. I even used it for cache replication (because who cares if it’s a cache miss, but a hit will save me time and money). It’s hard to make such blue prints in early days of product, and by the time you hit a true growth almost everyone builds a custom solution for multi-region IAM.

Amazing I was just looking for a good mail server to configure for my demo. Which reminds me since you folks have mentioned LiteStream, have you tried Marmot (https://github.com/maxpert/marmot); I recently configured Isso with Marmot to scale it out horizontally (https://maxpert.github.io/marmot/demo). I am super curious what kind of write workload on a sub thousand people organization will have and if Marmot can help scale it horizontally without Foundation DB. I always find the the convenience of SQLite amazing.

Great that you brought it up. I will fill in the perspective of what I am doing for solving this in Marmot (https://github.com/maxpert/marmot). Today Marmot already records changes via installing triggers to record changes of a table, hence all the offline changes (while Marmot is not running) are never lost. Today when Marmot comes up after a long offline (depending upon max_log_size configuration), it realizes that and tries to catch up changes via restoring a snapshot and then applying rest of logs from NATS (JetStream) change logs. I am working on change that will be publishing those change logs to NATS before it restores snapshots, and once it reapplies those changes after restoring snapshot everyone will have your changes + your DB will be up to date. Now in this case one of the things that bothers people is the fact that if two nodes coming up with conflicting rows the last writer wins.

For that I am also exploring on SQLite-Y-CRDT (https://github.com/maxpert/sqlite-y-crdt) which can help me treat each row as document, and then try to merge them. I personally think CRDT gets harder to reason sometimes, and might not be explainable to an entry level developers. Usually when something is hard to reason and explain, I prefer sticking to simplicity. People IMO will be much more comfortable knowing they can't use auto incrementing IDs for particular tables (because two independent nodes can increment counter to same values) vs here is a magical way to merge that will mess up your data.

Hi HN, I’m Kyle and together with Andrew (https://news.ycombinator.com/user?id=stanleydrew) we’ve been working on Riza (https://riza.io), a project to make WASM sandboxing more approachable. We’re excited to share a developer preview of our code interpreter API with HN.

There’s a bit of a backstory here. A few months ago, an old coworker reached out asking how to execute untrusted code generated by an LLM. Based on our experience building a plugin system for sqlc (https://sqlc.dev), we thought a sandboxed WASM runtime would be a good fit. A bit of hacking later, we got everything wired up to solve his issue. Now the API is ready for other developers to try out.

The Riza Code Interpreter API is an HTTP interface to various dynamic language interpreters, each running inside a WASM sandbox without access to the outside world (for now). We modeled the API to align with a POSIX shell-style interface.

We made a playground so you can try it out without signing up: https://riza.io

The API documentation lives here: https://docs.riza.io

There are many limitations at the moment, but we expect to rapidly expand capabilities so that programs can e.g. access the network and filesystem. Our roadmap has more details: https://docs.riza.io/reference/roadmap

If you need to execute LLM-generated code we’d love to have you try the API and let us know if you run into any issues. You can email us directly at [email protected].

"Is there a way to get sqlc to use pointers for nullable columns instead of the sql.Null types?"

I came across this yesterday for golang: https://sqlc.dev which is somewhat like what you want, maybe.

Not sure it allows you to parameterize table names but the basic idea is codegen from sql queries so you are working with go code (autocompletion etc).

Agreed, but tools like https://sqlc.dev, which I mention in the article, are a good trade-off that allows you to have verified, testable, SQL in your code.

sqlc is not strictly a conventional ORM. It offers a unique approach by generating Go code from SQL queries. This allows developers to write SQL, which sqlc then converts into type-safe Go code, reducing the boilerplate significantly. It ensures that your queries are syntactically correct and type-safe. sqlc is ideal for those who prefer writing SQL and are looking for an efficient way to integrate it into a Go application.

I was browsing awesome-go for ideas on how to setup my data access layer when I stumbled on sqlc. It seemed like a great option. Code generation is a strategy often used in the Go ecosystem and making my queries safe at compile time was an idea I really liked. Knex was great, but it required of me that I test thoroughly my queries at runtime and that I sanitize my query results to ensure type safety within my application.

Now, we are going to generate the code. For this purpose, we are going to use sqlc.

https://github.com/sqlc-dev/sqlc — for use with //go:generate