risingwave
arroyo
| risingwave | arroyo | |
|---|---|---|
| 27 | 13 | |
| 6,309 | 3,293 | |
| 2.2% | 2.3% | |
| 10.0 | 9.6 | |
| 5 days ago | 1 day ago | |
| Rust | Rust | |
| Apache License 2.0 | Apache License 2.0 |
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.
risingwave
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Proton, a fast and lightweight alternative to Apache Flink
How does this compare to RisingWave and Materialize?
https://github.com/risingwavelabs/risingwave
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RisingWave's Roadmap - Redefining Stream Processing with the Rust-Built Streaming Database
Hey everyone - One and a half year ago, we open sourced RisingWave, a Rust-built streaming database, under Apache 2.0 license. Two weeks ago, we released RisingWave 1.3. Just last week, we unveiled RisingWave's roadmap.
- Risingwave: Redefining Stream Processing
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Highlights of RisingWave v1.3: The Open-Source Streaming Database
Look out for next month’s edition to see what new, exciting features will be added. Check out the RisingWave GitHub repository to stay up to date on the newest features and planned releases.
- Optimizing Rust Code for the Lsm-Tree Iterator in RisingWave
- Hummock: A Storage Engine Designed for Stream Processing
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RisingWave 1.2 released - the open-source streaming database built in Rust
If interested, please feel free to join our Slack community! Thanks eveyone for your generous support!
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Query materialized views with Java, Spring, and streaming database
We will spin up on our local environment the existing RisingWave fully-featured demo cluster on GitHub which is composed of multiple RisingWave components. To simplify this task, it leverages docker-compose.yaml file which includes additional containers for Kafka message broker, and data generation service.
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Real-time Data Processing Pipeline With MongoDB, Kafka, Debezium And RisingWave
To complete the steps in this guide, you must download/clone and work on an existing sample project on GitHub. The project uses Docker for convenience and consistency. It provides a containerized development environment that includes the services you need to build the sample data pipeline.
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Flink CDC / alternatives
Hey have you looked at RisingWave (https://github.com/risingwavelabs/risingwave) before? It's a stream processing system with PostgreSQL interface. It also have integrations similar to Flink CDC.
arroyo
- FLaNK AI Weekly 18 March 2024
- Arryo 0.8 released — streaming SQL engine
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Query Engines: Push vs. Pull
Interesting - I looked into your code a bit. I found your window aggregation library [1]. You may be interested in looking into the Rust implementation of some of the research work I've been a part of [2].
In Flink, I believe the reason they need to implement their own backpressure system is that they multiplex TCP connections. That is, they have multiple logical streams flowing through a single TCP connection. If that's the case, you need to do some work to 1) detect which logical stream is the one that's blocking, and 2) don't block because other logical streams may be able to use the active TCP connection.
Thinking it through, I think what Flink's approach buys is not necessarily better performance, but better just a manageable number of connections. That is, imagine you have a process P1 with operators A, B and C. And then P2 has D, E, F. Now imagine that this is a shuffle, where A, B and C are fully connected to D, E and F. In my old system, you would have 9 TCP connections. In Flink, you will have 1.
[1] https://github.com/ArroyoSystems/arroyo/blob/master/arroyo-w...
- Arroyo
- Show HN: Arroyo – Write SQL on streaming data
- Release v0.3.0 · ArroyoSystems/arroyo - Stream Processing Engine
- Arroyo 0.2 released - Rust stream processing engine, now on Kubernetes
- Distributed stream processing engine written in Rust
- ArroyoSystems/arroyo: Arroyo is a distributed stream processing engine written in Rust
- Arroyo, a new open-source SQL stream processing engine written in Rust
What are some alternatives?
materialize - The data warehouse for operational workloads.
bytewax - Python Stream Processing
datafuse - An elastic and reliable Cloud Warehouse, offers Blazing Fast Query and combines Elasticity, Simplicity, Low cost of the Cloud, built to make the Data Cloud easy [Moved to: https://github.com/datafuselabs/databend]
Benthos - Fancy stream processing made operationally mundane
ksql - The database purpose-built for stream processing applications.
cli - Railway CLI
greptimedb - An open-source, cloud-native, distributed time-series database with PromQL/SQL/Python supported. Available on GreptimeCloud.
feldera - Feldera Continuous Analytics Platform
chdb - chDB is an embedded OLAP SQL Engine 🚀 powered by ClickHouse
timely-dataflow - A modular implementation of timely dataflow in Rust
roapi - Create full-fledged APIs for slowly moving datasets without writing a single line of code.
sqlglot - Python SQL Parser and Transpiler