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Hm. I normally use github.com/pgautoupgrade/docke whenever I need to deploy a #postgres container because I can just increase the version in my #Ansible playbooks to perform an upgrade.

Now I need #postgis for #dawarich and there doesn't seem to be such a convenient fork to ease future upgrades.

Am I missing something? Do I really want to bother future-me with manual upgrades that may include dumping, updating and restoring? Or would I just add these steps to my playbook?

GitHubGitHub - pgautoupgrade/docker-pgautoupgrade: A PostgreSQL Docker container that automatically upgrades your databaseA PostgreSQL Docker container that automatically upgrades your database - pgautoupgrade/docker-pgautoupgrade

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Antwortete im Thread

A l'heure où l'on parle de souveraineté sur l'ensemble des services numériques, l'information géographique a atteint un niveau de maturité incroyable.
La gestion des données spatiales de référence de Finlande bascule sur des technologies open source et libres. #QGIS et #postgresql #postgis au moins au menu.
L'ouverture des formats de données, l'intéropérabilité, la mutualisation sur les outils avec les autorités publiques sont mises en avant :

positio-magazine.eu/2025/06/fi

Positio · Finland Launches Modern Topographic Data System – Built on Open-Source QGIS | PositioThis new open-source based system enables more efficient and up-to-date maintenance of the national topographic data and the production of general map products.

MDS in geo: An example with Mapillary: Two articles by Michaël Galien on @geotribu showcase how to leverage a Modern Data Stack (#MDS) for processing geospatial data from #Mapillary. The workflow features #dbt, Apache #Airflow, #PostGIS, #SQL, and #Python, highlighting a robust...
spatialists.ch/posts/2025/06/0 #GIS #GISchat #geospatial #SwissGIS

Spatialists – geospatial newsMDS in geo: An example with Mapillary – Spatialists – geospatial news
Mehr von Spatialists

#RStats #PostgreSQL #PostGIS question!

Is there a sensible -- no, *ideal* -- way to store spatiotemporal raster/NetCDFs in a PostgreSQL database? Ideally one which can still be easily queried in R.

My default approach of just converting them into dataframes and pushing everything to a database a) seems very inefficient, and b) *definitely* takes up more space than we have available in the database.

I think we could technically ask for more space, and insert indices to make using that data faster, but...seems like the wrong direction and not worth the effort.