cr-sqlite VS neon

I'm a happy user of https://github.com/vlcn-io/cr-sqlite/

If you're interested in this, here are some related projects that all take slightly different approaches:

- LiteSync directly competes with Marmot and supports DDL sync, but is closed source commercial (similar to SQLite EE): https://litesync.io

- dqlite is Canonical's distributed SQLite that depends on c-raft and kernel-level async I/O: https://dqlite.io

- cr-sqlite is a Rust-based loadable extension that adds CRDT changeset generation and reconciliation to SQLite: https://github.com/vlcn-io/cr-sqlite

Slightly related but not really (no multi writer, no C-level SQLite API or other restrictions):

- comdb2 (Bloombergs multi-homed RDMS using SQLite as the frontend)

- rqlite: RDMS with HTTP API and SQLite as the storage engine, used for replication and strong consistency (does not scale writes)

- litestream/LiteFS: disaster recovery replication

- liteserver: active read-only replication (predecessor of LiteSync)

Theory is great, but how can we apply this in practice? Instead of starting from 0, and writing a CRDT, let's try and leverage an existing project to do the heavy lifting. My choice is crSQLITE, an extension for SQLite to support CRDT merging of databases. Under the hood, the extension creates tables to track changes and allow inserting into an event log for merging states of separated peers.

Also https://github.com/vlcn-io/cr-sqlite/ which is SQLite + CRDTs

Runs/syncs to the browser too which is just lovely.

If you need multiple writers and can handle eventual correctness, you should really be using cr-sqlite[1]. It'll allow you to have any number of workers/clients that can write locally within the same process (so no network overhead) but still guarantee converge to the same state.

[1] https://github.com/vlcn-io/cr-sqlite

I am fully on the offline-first bandwagon after starting to use cr-sqlite (https://vlcn.io), which works similar to ElectricSQL.

I thought the bundle size of wasm-sqlite would be prohibitive, but it's surprisingly quick to download and boot. Reducing network reliance solves so many problems and corner-cases in my web app. Having access to local data makes everything very snappy too - the user experience is much better. Even if the user's offline data is wiped by the browser (offline storage limits are a bit of a minefield), it is straightforward to get all synced changes back from the server.

I didn't know that. Especially the first approach sounds interesting to me, because as far as I know the transactions of Yjs seem to be a problem on heavily changing documents. https://github.com/vlcn-io/cr-sqlite#approach-1-history-free... Thanks!

I wonder how this compares to https://vlcn.io?

The short ask: Anyone know of any projects that bring incremental view maintenance to SQLite?

The why:

Applications are usually read heavy. It is a sad state of affairs that, for these kinds of apps, we don't put more work on the write path to allow reads to benefit.

Would the whole No-SQL movement ever even have been a thing if relational databases had great support for materialized views that updated incrementally? I'd like to think not.

And more context:

I'm working to push the state of "functional relational programming" [1], [2] further forward. Materialized views with incremental updates are key to this. Bringing them to SQLite so they can be leveraged one the frontend would solve this whole quagmire of "state management libraries." I've been solving the data-sync problem in SQLite (https://vlcn.io/) and this piece is one of the next logical steps.

If nobody knows of an existing solution, would love to collaborate with someone on creating it.

[1] - https://github.com/papers-we-love/papers-we-love/blob/main/design/out-of-the-tar-pit.pdf

If you're reading this you probably got a really steep bill from Neon after finding yourself on their "Scale" plan. If you do want to stay with Neon but avoid surprise bills then go to the Plans page and choose what you actually want.

Such is the case with Neon, a serverless Postgres service, that went generally available on April 15. Congrats Nikita Shamgunov and team on the launch. When I saw the announcement, I knew I had to try it out for myself and report back with my findings.

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?

Neon is an open source and cloud-native serverless database platform that focuses on simplicity and ease of use. It supports Postgres databases and offers built-in features like bottomless storage, autoscaling, and branching.

For MySQL, we've got PlanetScale, and for PostgreSQL, there's Neon.

8. https://neon.tech/As you might know not one tool fits all, I still have strong preferences for the following. It helps me get going faster and get things done right first time and helps in ease of maintenance.

Language: Typescript.

Migrated away when they removed the free tier, ended up using https://neon.tech/

Cool! At Neon[0], I work full time on our custom postgres proxy[1]. It's a very nice protocol to work with, although our usecase is quite a bit more complex compared to the ideas presented in the post.

Neon databases scale to zero, so the proxy needs to spin up databases on the fly. The proxy doesn't do that but it knows if the databases is running and asks our control plane to schedule it if it isn't. It's a fun service to maintain.

The biggest pain is error handling. Postgres is really bad for error messages and codes. The only available code we can use is usually protocol violation...

[0]: https://neon.tech/

Neon - PostgreSQL