differential-datalog
timely-dataflow
differential-datalog | timely-dataflow | |
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22 | 11 | |
1,340 | 3,180 | |
0.5% | 1.6% | |
0.0 | 7.0 | |
10 months ago | 7 days ago | |
Java | Rust | |
MIT License | MIT License |
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differential-datalog
- DDlog: A programming language for incremental computation
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Feldera – a more performant streaming database based on Z-sets
Hi,
> I wonder if it lives up to the hype.
We do think so! (disclaimer: I'm a co-founder at Feldera)
To give some more background: We are co-designing/trialing feldera with several industry/enterprise partners from different domains. Our core team also built differential datalog (https://github.com/vmware/differential-datalog) in the past. And while ddlog is used quite successfully in products today, we believe the many lessons we learned with ddlog will help us to build an even better continuous analytics platform. FYI our code is open-source at https://github.com/feldera/feldera if you'd like to try it out.
Also feel free to join our community slack channel (https://www.feldera.com/slack/) if you have more questions.
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Why Are There No Relational DBMSs? [pdf]
The relational model (and generally working at the level of sets/collections, instead of the level of individual values/objects) actually makes it easier to have this kind of incremental computation in a consistent way, I think.
There's a bunch of work being done on making relational systems work this way. Some interesting reading:
- https://www.scattered-thoughts.net/writing/an-opinionated-ma...
- https://materialize.com/ which is built on https://timelydataflow.github.io/differential-dataflow/, which has a lot of research behind it
- Which also can be a compilation target for Datalog: https://github.com/vmware/differential-datalog
- Some prototype work on building UI systems in exactly the way you describe using a relational approach: https://riffle.systems/essays/prelude/ (and HN discussion: https://news.ycombinator.com/item?id=30530120)
(There's a lot more too -- I have a hobby interest in this space, so I have a small collection of links)
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Differential Datalog: a programming language for incremental computation
Tutorial which I didn’t see linked in the README: https://github.com/vmware/differential-datalog/blob/master/d...
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Show HN: Cozo – new Graph DB with Datalog, embedded like SQLite, written in Rust
This is amazing!
Have you looked at differential-datalog? It's rust-based, maintained by VMWare, and has a very rich, well-typed Datalog language. differential-datalog is in-memory only right now, but could be ideal to integrate your graph as a datastore or disk spill cache.
https://github.com/vmware/differential-datalog
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Help wanted!
Sort of related, in my mind at least, is differential dataflow, e.g. https://github.com/vmware/differential-datalog
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Datalog in JavaScript
It’s fascinating to see so many different parties converging on Datalog for reactive apps & UI.
- There are several such talks at https://www.hytradboi.com/ (happening this Friday)
- Roam Research and its clones Athens, Logseq, use Datascript / ClojureScript https://github.com/tonsky/datascript
- differential-datalog isn’t an end-to-end system, but is highly optimized for quick reactivity https://github.com/vmware/differential-datalog
- Datalog UI is a Typescript port of some of differential-datalog’s ideas https://datalogui.dev/
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Call for Help - Open Source Datom/EAV/Fact database in Rust.
Rust related https://github.com/vmware/differential-datalog
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Anything like Svelte/Jetpack Compose for Haskell?
Actually, that makes me wonder whether or not differential datalog falls under that umbrella, and if it could be applied in the same way Compose is.
timely-dataflow
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Readyset: A MySQL and Postgres wire-compatible caching layer
They have a bit about their technical foundation here[0].
Given that Readyset was co-founded by Jon Gjengset (but has apparently since departed the company), who authored the paper on Noria[1], I would assume that Readyset is the continuation of that research.
So it shares some roots with Materialize. They have a common conceptual ancestry in Naiad, where Materialize evolved out of timely-dataflow.
[0]: https://docs.readyset.io/concepts/streaming-dataflow
[1]: https://jon.thesquareplanet.com/papers/osdi18-noria.pdf
[2]: https://dl.acm.org/doi/10.1145/2517349.2522738
[3]: https://github.com/TimelyDataflow/timely-dataflow
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Mandala: experiment data management as a built-in (Python) language feature
And systems like timely dataflow, https://github.com/TimelyDataflow/timely-dataflow
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Arroyo: A distributed stream processing engine written in Rust
Project looks cool! Glad you open sourced it. It could use some comments in the code base to help contributors ;). I also like the datafusion usage, that is awesome. BTW I work on github.com/bytewax/bytewax, which is based on https://github.com/TimelyDataflow/timely-dataflow another Rust dataflow computation engine.
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Rust MPI -- Will there ever be a fully oxidized implementation?
Just found this https://github.com/TimelyDataflow/timely-dataflow and my heart skipped a beat.
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Streaming processing in Python using Timely Dataflow with Bytewax
Bytewax is a Python native binding to the Timely Dataflow library (written in Rust) for building highly scalable streaming (and batch) processing pipelines.
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Alternative Kafka Integration Framework to Kafka Connect?
I am working on Bytewax, which is a Python stream processing framework built on Timely Dataflow. It is not exactly a Kafka integration framework because it is a more of a general stream processing framework, but might be interesting for you. We are focused on enabling people to more easily debug, containerize, parallelize and customize and less on enabling a declarative integration framework. It is still early days for us! And we are looking for feedback and ideas from the community.
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[AskJS] JavaScript for data processing
We used to use a library called Pond.js, https://github.com/esnet/pond, but the reliance on Immutable.JS caused some performance pitfalls, so we wrote a system from scratch that deals with data in a batched streaming fashion. A lot of the concepts were borrowed from a Rust library called timely-dataflow, https://github.com/TimelyDataflow/timely-dataflow.
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Dataflow: An Efficient Data Processing Library for Machine Learning
Though the name "Dataflow" might be an unfortunate name conflict with another Rust project: https://github.com/TimelyDataflow/timely-dataflow
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Ask HN: Is there a way to subscribe to an SQL query for changes?
> In the simplest case, I'm talking about regular SQL non-materialized views which are essentially inlined.
I see that now -- makes sense!
> Wish we had some better database primitives to assemble rather than building everything on Postgres - its not ideal for a lot of things.
I'm curious to hear more about this! We agree that better primitives are required and that's why Materialize is written in Rust using using TimelyDataflow[1] and DifferentialDataflow[2] (both developed by Materialize co-founder Frank McSherry). The only relationship between Materialize and Postgres is that we are wire-compatible with Postgres and we don't share any code with Postgres nor do we have a dependence on it.
[1] https://github.com/TimelyDataflow/timely-dataflow
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7 Real-Time Data Streaming Tools You Should Consider On Your Next Project
Under the hood, Materialize uses Timely Dataflow (TDF) as the stream-processing engine. This allows Materialize to take advantage of the distributed data-parallel compute engine. The great thing about using TDF is that it has been in open source development since 2014 and has since been battle-tested in production at large Fortune 1000-scale companies.
What are some alternatives?
scryer-prolog - A modern Prolog implementation written mostly in Rust.
noria - Fast web applications through dynamic, partially-stateful dataflow
materialize - The data warehouse for operational workloads.
differential-dataflow - An implementation of differential dataflow using timely dataflow on Rust.
bytewax - Python Stream Processing
datalevin - A simple, fast and versatile Datalog database
realtime - Broadcast, Presence, and Postgres Changes via WebSockets
logica - Logica is a logic programming language that compiles to SQL. It runs on Google BigQuery, PostgreSQL and SQLite.
diagnostics - Diagnostic tools for timely dataflow computations
flow - 🌊 Continuously synchronize the systems where your data lives, to the systems where you _want_ it to live, with Estuary Flow. 🌊