beam VS ihp

The "streaming systems" book answers your question and more: https://www.oreilly.com/library/view/streaming-systems/97814.... It gives you a history of how batch processing started with MapReduce, and how attempts at scaling by moving towards streaming systems gave us all the subsequent frameworks (Spark, Beam, etc.).

As for the framework called MapReduce, it isn't used much, but its descendant https://beam.apache.org very much is. Nowadays people often use "map reduce" as a shorthand for whatever batch processing system they're building on top of.

Apache Beam is one of many tools that you can use

Flexible runtime ☁️: Temporian programs can run seamlessly in-process in Python, on large datasets using Apache Beam.

To perform the tests I'm using a Kafka cluster on Kubernetes from the Beam repo (here).

Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow

Apache Beam: Batch/streaming data processing 🔗Link

What you are looking for is Dataflow. It can be a bit tricky to wrap your head around at first, but I highly suggest leaning into this technology for most of your data engineering needs. It's based on the open source Apache Beam framework that originated at Google. We use an internal version of this system at Google for virtually all of our pipeline tasks, from a few GB, to Exabyte scale systems -- it can do it all.

That being said, there is a learning curve in understanding how Apache Beam works. Take a look at the beam website for more information.

I found IHP straightforward:

https://ihp.digitallyinduced.com/

despite not remembering much haskell!

This assumes you can get past nix for the install.

I find IHP well-designed. I just wish the licensing scheme were more transparent.

You can find the docs at https://ihp.digitallyinduced.com/ and some getting started videos at https://www.youtube.com/watch?v=PLl9Sjq6Nzc&list=PLenFm8BWuKlS0IaE31DmKB_PbkMLmwWmG

In case this got you interested in Haskell, and you want a good way to start your Haskell journey (and have something to apply the optimization handbook to), check out IHP. It's the Rails/Laravel of the Haskell world. You can start here https://ihp.digitallyinduced.com/Guide/index.html or check it out on GitHub here https://github.com/digitallyinduced/ihp

At IHP we've been using Algora for a while now and it works really great. Here's e.g. one PR that was merged last week with a bounty attached https://github.com/digitallyinduced/ihp/issues/1621 Everything was set up in less than 15 minutes and ioannis and zafer have been super helpful with any questions we had.

In general I think this is a good direction and an interesting take on the open question around sustainable open source. Congrats on the launch and keep up the great work! :)

You could contribute to IHP! We have some great docs to get started here https://github.com/digitallyinduced/ihp/blob/master/CONTRIBUTING.md And we have some low hanging fruits in GitHub issues for you to get started with, e.g. https://github.com/digitallyinduced/ihp/issues/1601 (also there's always lots of activity in the IHP Slack, in case you have any questions/need help)