beam VS podman

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.

Example of why: https://github.com/containers/podman/issues/5102#issuecommen...

Podman

Even though we will focus on Docker for this article, I wanted to mention that there are more container creation and management tools such as Podman, Rkt, and so on.

By using containerization, the application will always have the same configuration that is used in the development environment and production environment. There is no more "It works on my machine". Some examples of containerization technologies are Docker and Podman.

Podman Documentation. Podman is a daemonless container engine for developing, managing, and running OCI Containers on your Linux System.

AFAIK podman either already supports pods in quadlet container files, or will in the near future. https://github.com/containers/podman/pull/20762

Podman as a devcontainers engine doesn't currently work if you use devcontainer features [1] or (and this sounds like you're issue) if you use WSL2.

I haven't submitted the WSL2 issue to the Podman team yet. If you get to it before I do, can you like it here?

https://github.com/containers/podman/issues/18691#issuecomme...

You can also use their Oracle Linux Docker images with the database preinstalled using either Podman or Docker. Just make absolutely sure you are downloading something you are licensed to use, because it seems really easy to accidentally infringe copyright via this method.

It's an open source project. https://github.com/containers/podman and https://podman.io - go there, get engaged, see what's going on and most important become part of the community and contribute!