rust-signals
differential-dataflow
rust-signals | differential-dataflow | |
---|---|---|
6 | 14 | |
594 | 2,486 | |
- | 1.3% | |
4.5 | 8.3 | |
about 1 month ago | 8 days ago | |
Rust | Rust | |
MIT License | MIT License |
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rust-signals
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A Proposal for an asynchronous Rust GUI framework
What is the relation and differences between this approach and rust-signals?
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A good/decently matured rxjs-based library?
Signals is a fantastic and stable library for reactive programming https://github.com/Pauan/rust-signals
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A first look at Sycamore's new reactive primitives: how the next version of Sycamore will be the most ergonomic yet
How does this approach differ from rust-signals? https://github.com/Pauan/rust-signals
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Announcing avalanche 0.1, a React- and Svelte-inspired GUI library
You might want to check out dominator and the rust-signals it is based on, seems like a similar technique to avalanche.
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Crate similar to Kotlin Flow?
Maybe try futures-signal? I think its API looks quite nice and it even has a tutorial.
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Rust on the front-end
Both are signal-based, which seems like the way to go to me. The latter seems more mature in terms of code, but also lacking in good documentation. The rust-signal crate it uses though has a nice tutorial from which a lot of concepts seem to transfer.
differential-dataflow
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We Built a Streaming SQL Engine
Some recent solutions to this problem include Differential Dataflow and Materialize. It would be neat if postgres adopted something similar for live-updating materialized views.
https://github.com/timelydataflow/differential-dataflow
https://materialize.com/
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Hydroflow: Dataflow Runtime in Rust
I'm looking for this but can't find it, how does this project compare to differential dataflow?
As a sibling commenter mentioned, it's built on timely dataflow (which is lower-level), but that already has differential dataflow[0] built on top of it by the same authors.
How do they differ?
[0]: https://github.com/TimelyDataflow/differential-dataflow
- Using Rust to write a Data Pipeline. Thoughts. Musings.
- PlanetScale Boost
- Program Synthesis is Possible (2018)
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Convex vs. Firebase
hi! sujay from convex here. I remember reading about your "reverse query engine" when we were getting started last year and really liking that framing of the broadcast problem here.
as james mentions, we entirely re-run the javascript function whenever we detect any of its inputs change. incrementality at this layer would be very difficult, since we're dealing with a general purpose programming language. also, since we fully sandbox and determinize these javascript "queries," the majority of the cost is in accessing the database.
eventually, I'd like to explore "reverse query execution" on the boundary between javascript and the underlying data using an approach like differential dataflow [1]. the materialize folks [2] have made a lot of progress applying it for OLAP and readyset [3] is using similar techniques for OLTP.
[1] https://github.com/TimelyDataflow/differential-dataflow
[2] https://materialize.com/
[3] https://readyset.io/
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Announcing avalanche 0.1, a React- and Svelte-inspired GUI library
differential dataflow which is used to power materialize db
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Differential Datalog
It's partially inspired by Linq, so the similarity you see is expected.
It's not really arbitrary structures so much, though you're mostly free in what record type you use in a relation (structs and tagged enums are typical, though).
The incremental part is that you can feed it changes to the input (additions/retractions of facts) and get changes to the outputs back with low latency (you can alternatively just use it to keep an index up-to-date, where you can quickly look up based on a key (like a materialized view in SQL)).
This [0] section in the readme of the underlying incremental dataflow framework may help get the concept across, but feel free to follow up if you're still not seeing the incrementality.
[0]: https://github.com/TimelyDataflow/differential-dataflow#an-e...
- Dbt and Materialize
- Materialized view questions
What are some alternatives?
rust-dominator - Zero-cost ultra-high-performance declarative DOM library using FRP signals for Rust!
ballista - Distributed compute platform implemented in Rust, and powered by Apache Arrow.
sycamore - A library for creating reactive web apps in Rust and WebAssembly
materialize - The data warehouse for operational workloads.
salsa - A generic framework for on-demand, incrementalized computation. Inspired by adapton, glimmer, and rustc's query system.
reflow - A language and runtime for distributed, incremental data processing in the cloud
sycamore-mac
differential-datalog - DDlog is a programming language for incremental computation. It is well suited for writing programs that continuously update their output in response to input changes. A DDlog programmer does not write incremental algorithms; instead they specify the desired input-output mapping in a declarative manner.
avalanche - Rust library for building performant Web apps
timely-dataflow - A modular implementation of timely dataflow in Rust
observe - Rust observables inspired by MobX
clj-3df - Clojure(Script) client for Declarative Dataflow.