katara
differential-dataflow
katara | differential-dataflow | |
---|---|---|
4 | 14 | |
130 | 2,486 | |
0.0% | 1.3% | |
0.7 | 8.3 | |
about 1 year ago | 8 days ago | |
Python | Rust | |
Apache License 2.0 | MIT License |
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katara
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Hydroflow: Dataflow Runtime in Rust
Oh, I realize this comes out the Hydro Project that produced a previous HN submission I thought was cool:
Katara is a project to synthesize CRDTs from a C++ implementation of a regular plain-old data structure along with a few annotations
https://news.ycombinator.com/item?id=32977887
https://github.com/hydro-project/katara
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This Week In Python
katara – Synthesize CRDTs from classic data types with verified lifting
- Katara: Synthesize CRDTs from Sequential Types
- Katara: Synthesizing CRDTs with Verified Lifting
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?
database-stream-processor - Streaming and Incremental Computation Framework
ballista - Distributed compute platform implemented in Rust, and powered by Apache Arrow.
puff - ☁ Puff ☁ - The deep stack framework.
materialize - The data warehouse for operational workloads.
koda-validate - Typesafe, Composable Validation
reflow - A language and runtime for distributed, incremental data processing in the cloud
django-pgtransaction - A context manager/decorator which extends Django's atomic function with the ability to set isolation level and retries for a given transaction.
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.
hydroflow - Hydro's low-level dataflow runtime
timely-dataflow - A modular implementation of timely dataflow in Rust
metalift - A program synthesis framework for verified lifting applications
clj-3df - Clojure(Script) client for Declarative Dataflow.