beam VS Redash

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.

It seems like there may be an issue with Watchdog on Apple Silicon.

I am looking for service or tool similiar to Metabase or Redash that allows me to add data source - for example Postgres connection, and create raw SQL queries that can be shared or exposed through API. So instead of keeping raw SQL code somewhere, my other service would call this tool e.g. http://microservice/query=1?param1=xx&page=2 and get the results from the DB. These calls are internal only and part of ETL processes, but of course authentication would be required.

Yeah, a lot of the time I'd agree with you.

This container came about for the Redash project (https://github.com/getredash/redash), which has been stuck on PostgreSQL 9.5 (!) for years.

Moving to a new PostgreSQL container version is easy enough for new installations, but rolling that kind of change out to an existing userbase isn't so pretty.

For people familiar with the command line, PostgreSQL, and Docker then no worries.

But a large number of Redash deployments seem to have been done by people not skilled in those things. "We deployed it from the Digital Ocean droplet / AWS image / etc!"

For those situations, something that takes care of the database upgrade process automatically is the better approach. :)

I have tried Metabase, Redash beore (both self hosted open source versions), from my experience I find Metabase a bit easy to work with.

Regarding visualization tools, sqliteviz has proven to be the best I've found so far. Their web app runs locally but has some trackers, so I run it locally via a simple, static HTTP server. Falcon and Redash seem like overkill for my needs.

Redash seems to be dead or at least in hibernation. There hasn't been a release in over a year.

https://github.com/getredash/redash/issues/5891

redash