readyset
differential-dataflow
readyset | differential-dataflow | |
---|---|---|
24 | 14 | |
3,882 | 2,473 | |
1.7% | 0.8% | |
9.8 | 8.3 | |
6 days ago | 6 days ago | |
Rust | Rust | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
readyset
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Ask HN: How Can I Make My Front End React to Database Changes in Real-Time?
- Some platforms like Supabase Realtime [3] and Firebase offer subscription models to database changes, but these solutions fall short when dealing with complex queries involving joins or group-bys.
My vision is that the modern frontend to behave like a series of materialized views that dynamically update as the underlying data changes. Current state management libraries handle state trees well but don't seamlessly integrate with relational or graph-like database structures.
The only thing I can think of is to implement it by myself, which sounds like a big PITA.
Anything goes, Brainstorm with me. Is it causing you headaches as well? Are you familiar with an efficient solution? how are you all tackling it?
[1] https://readyset.io/
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FLaNK Stack 26 February 2024
Postgresql + MySQL Cache https://github.com/readysettech/readyset
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Readyset: A MySQL and Postgres wire-compatible caching layer
I just wanted to give a high five for having Jepsen tests for this: https://github.com/readysettech/readyset/tree/stable-240117/...
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Fine-grained caching strategies of dynamic queries
This example is a great use case for partial incremental view maintenance systems like ReadySet: you automatically get something like the “prepopulating the cache” section (toward the end of the blog) while only caching the data the application is using, and avoiding the need to manually implement any sort of invalidation logic.
(Disclaimer: I used to work for them, but don’t anymore. It’s all available for free on GitHub though for anyone interested: https://github.com/readysettech/readyset)
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Squeeze the hell out of the system you have
There are systems that will do that for you like https://readyset.io/.
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Production grade databases in Rust
ReadySet
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Dozer: A scalable Real-Time Data APIs backend written in Rust
readyset.io is the company that jonhoo was associated with for work on noria
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I'm building Memories, a FOSS alternative to Google Photos with a focus on UX and performance
Might be interesting to try out https://readyset.io for this use case.
- Materialized View: SQL Queries on Steroids
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Tips on scaling a monolithic Rust web server?
On the caching topic, I found the ReadySet(né Noria) approach to be extremely interesting.
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?
materialize - The data warehouse for operational workloads.
ballista - Distributed compute platform implemented in Rust, and powered by Apache Arrow.
noria - Fast web applications through dynamic, partially-stateful dataflow
singleflight - Rust port of Go's singleflight package
reflow - A language and runtime for distributed, incremental data processing in the cloud
chiselstrike - ChiselStrike abstracts common backends components like databases and message queues, and let you drive them from a convenient TypeScript business logic layer
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.
googleapis - Public interface definitions of Google APIs.
timely-dataflow - A modular implementation of timely dataflow in Rust
genSQL - A SQL generator tool to create random rows for test schemas
clj-3df - Clojure(Script) client for Declarative Dataflow.