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Love the small footprint, more databases should have this, I've recently gotten into building some applications with SQLite and its been a blast.

I went through the FAQ and read through the README on the github page, however I'm unable to figure out some really ideal usecases for proton. Ideally from a product perspective.

I like to have some examples so when I am building in the future I can quickly know off the top of my head, "oh yeah, lets just use proton for this."

Does anyone have a few different applications types which they've built or problems they've solved with proton? Bonus points for external examples with some code.



Thanks for the feedback (I am part of the Timeplus team)

https://docs.timeplus.com/showcases lists a few real world use cases we solve with our customers. Proton is core engine of Timeplus Cloud, which adds extra UI, sources/sinks, multi-tenant etc.

https://docs.timeplus.com/proton-howto lists some of the common tasks for processing real-time data. Basically if you're in the data engineering space, Proton can do many things that Flink/Spark/ksqlDB can do, just faster and more lightweight.

Good point of "oh yeah, lets just use proton for this." Will add more docs and examples for such newly-open-sourced project (we have ran the cloud service for 1.5 years)


Great points! SQLite as an analogy is fantastic for its small footprint. Swift download, deployment, and testing significantly boost dev productivity. Moreover, the dependency-free single-binary can efficiently slash deployment and operational costs. In addition to its outstanding performance, Proton users are specifically requesting data streaming processing, routing, analytics, and actions at the edge or in a hybrid environment before sending to their centralized data warehouses. This stands out as unique capabilities compared to existing complicated stacks.


(PS I am one of the contributors of Timeplus Proton. What I said could be biased.) Thanks for the feedbacks and they totally make sense. We will definitely work on the README, FAQ etc to make key use cases etc more explicit.

A very typical scenario is live query / analysis data in Kafka topics with Proton Streaming SQL and materialize the processed / aggregated results to a downstream system like ClickHouse or a target Kafka topic. What we need to do is 1. curl download the binary 2. create an external stream to point to your Kafka topic 3. run the streaming SQL.


Redpanda Proton ClickHouse: A perfect match as a single-binary approach for a lightweight and high-performance data streaming processing and analytics in one compact box!




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