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Update 'Open source business analytics tools'

Guillem Borrell Nogueras 2023-02-19 12:41:03 +01:00
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Open-source-business-analytics-tools.md

@ -2,7 +2,7 @@ I've used many free, hosted, locked... business analytics tools already and all
## Metabase ## Metabase
I started using database in projects around the end of '19. I liked its simple-but-get-stuff-done approach. The no-code interface feels unintuitive at first, and you will be confused sometimes about how dashboard-global filters work. But if I had to choose something really great about Metabase is that it's incredibly simple to deploy and it's probably the most efficient business analytics tool that there is. I started using database in projects around the end of '19. I liked its simple-but-get-stuff-done approach. The no-code interface feels unintuitive at first, and you will be confused sometimes about how dashboard-global filters work. But if I had to choose something really great about Metabase is that it's incredibly simple to deploy and it's probably the most efficient business analytics tool that there is. Cpu and memory pressure is always ridiculously low, it really does a great job at pushing the load to the database, like it's not doing any serialization.
You deploy Metabase, not a service that needs some additional cache, a task queue... You just deploy a container with Metabase, point requests to the corresponding port, configure the database connectors, and that's it. It is really a component that you can get up and running in your stack in no time. You deploy Metabase, not a service that needs some additional cache, a task queue... You just deploy a container with Metabase, point requests to the corresponding port, configure the database connectors, and that's it. It is really a component that you can get up and running in your stack in no time.
@ -12,7 +12,7 @@ Metabase has a paid edition with some additional features. The most relevant of
Metabase was my confort zone until I needed some advanced geo representation and I tried Superset. It's harder to install; I remember struggling for a a couple of hours to get dependencies right for 2.0. I then packaged them in a script so I could have reproducible installs, but nothing close to the absolute simplicity of Metabase. Metabase was my confort zone until I needed some advanced geo representation and I tried Superset. It's harder to install; I remember struggling for a a couple of hours to get dependencies right for 2.0. I then packaged them in a script so I could have reproducible installs, but nothing close to the absolute simplicity of Metabase.
The instructions recommend installing Superset with Celery and some cache, either Memcached or Redis. I've never installed them and the server could always sustain the load of teams of 5-6 analysts and consultants with 4 gunicorn workers. The instructions recommend installing Superset with Celery and some cache, either Memcached or Redis. I've never installed them and the server could always sustain the load of teams of 5-6 analysts and consultants with 4 gunicorn workers. But these workers hit 100% of cpu load often.
It's more powerful but less polished than Metabase in almost every single aspect. It's trivial to understand who has access to which dataset or dashboard with Metabase, but Superset's fine-grain permissions are harder to understand, and you need some careful reading to understand how they work. It's more powerful but less polished than Metabase in almost every single aspect. It's trivial to understand who has access to which dataset or dashboard with Metabase, but Superset's fine-grain permissions are harder to understand, and you need some careful reading to understand how they work.