crdt-benchmarks VS cr-sqlite

Author of Yjs here. I'm all for faster data structures. But only benchmarking one dimension looks quite fishy to me. A CRDT needs to be adequate at multiple dimensions. At least you should describe the tradeoffs in your article.

The time to insert characters is the least interesting property of a CRDT. It doesn't matter to the user whether a character is inserted within .1ms or .000000001ms. No human can type that fast.

It would be much more interesting to benchmark the time it takes to load a document containing X operations. Yjs & Yrs are pretty performant and conservative on memory here because they don't have to build an index (it's a tradeoff that we took consciously).

When benchmarking it is important to measure the right things and interpret the results somehow so that you can give recommendations when to use your algorithm / implementation. Some things can't be fast/low enough (e.g. time to load a document, time to apply updates, memory consumption, ..) other things only need to be adequate (e.g. time to insert a character into a document).

Unfortunately, a lot of academic papers set a bad trend of only measuring one dimension. Yeah, it's really easy to succeed in one dimension (e.g. memory or insertion-time) and it is very nice click-bait. But that doesn't make your CRDT a viable option in practice.

I maintain a set of benchmarks that tests multiple dimensions [1]. I'd love to receive a PR from you.

[1]: https://github.com/dmonad/crdt-benchmarks

Diamond types author here! Congratulations on getting your crdt working! It’s lovely to see a new generation of CRDTs which have decent performance.

And nice stuff implementing peritext! I’d love to do the same in diamond types at some point. You beat me to it!

Im building a little repository of real world collaborative editing traces to use when benchmarking, comparing and optimising text based CRDTs[1]. The automerge-perf editing trace isn’t enough on its own. And we’re increasingly converging on a format for multi user concurrent editing traces too[2]. It’d be great to add some rich text editing traces in the mix if you’re interested in recording something, so we can also compare how peritext performs in different systems.

Anyway, welcome to the community! Love to have more implementations around!

https://github.com/josephg/crdt-benchmarks

https://github.com/dmonad/crdt-benchmarks/issues/20

So yes, a particularly large document is not the norm but it can happen.

JavaScript CRDTs can be quite performant, see the Yjs benchmarks: https://github.com/dmonad/crdt-benchmarks

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