revori
timely-dataflow
revori | timely-dataflow | |
---|---|---|
1 | 11 | |
10 | 3,157 | |
- | 0.9% | |
0.0 | 7.0 | |
over 9 years ago | 11 days ago | |
Java | 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.
revori
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Ask HN: Is there a way to subscribe to an SQL query for changes?
I've implemented a RDBMS that supports this [1]. It handles joins, views (which are automatically materialized and incrementally updated), etc. It's memory only, and it doesn't support exotic stuff like recursive CTEs, but it does exactly what you're asking for. We used it in production successfully for frequently-updated real time data at the company where I used to work.
Notably, it uses persistent search trees such that each revision shares structure with the previous one, which makes diffing two closely-related revisions extremely efficient (just skip over any shared structure). Subscribers just receive a stream of diffs, with backpressure handled automatically by skipping over intermediate revisions. See [2] for a more detailed summary.
It also exposes revisions as first-class objects, which allows you to tag and diff them. Specifically, you can run arbitrary queries on both revisions and diffs. See [3] for examples.
It's no longer maintained, unfortunately. Someday I may revive it, perhaps adding support for spilling data that won't fit in memory to log-structured merge trees. I'd also rewrite it in a language like Rust, which will help flatten some of the more pointer-heavy data structures and reduce tail latencies. If anyone is interested in seeing that happen or helping out, let me know.
I'm really surprised this still isn't supported in mainstream DBMSes. The MVCC model in PostgreSQL seems particularly well suited to it.
[1]: https://github.com/ReadyTalk/revori
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?
rethinkdb_rebirth - The open-source database for the realtime web.
noria - Fast web applications through dynamic, partially-stateful dataflow
cainophile
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.
pg-live-select - Live Updating PostgreSQL SELECT statements
materialize - The data warehouse for operational workloads.
PipelineDB - High-performance time-series aggregation for PostgreSQL
bytewax - Python Stream Processing
flow - 🌊 Continuously synchronize the systems where your data lives, to the systems where you _want_ it to live, with Estuary Flow. 🌊
realtime - Broadcast, Presence, and Postgres Changes via WebSockets
differential-dataflow - An implementation of differential dataflow using timely dataflow on Rust.