PMTiles VS geos

I am a novice at GIS and mapping but when I got started I thought a map/tile server was the only way to build mapping webapps.

But, in my admittedly simple application PMTiles can cover a lot of my visualization use cases with a thing Django app doing GEOJson for interactive stuff.

https://github.com/protomaps/PMTiles

This is awesome. Such a great use case for nix.

I do a lot of geospatial processing in the cloud and I've been using Tippecanoe a lot to create vector tiles. It pairs well with PM Tiles for storing on the cloud. It seriously increases the web app performance for massive data sets. I queue these up with ECS tasks to process our json/csv/parquet input and create optimize vector tile outputs.

https://github.com/felt/tippecanoe

https://github.com/protomaps/PMTiles

Tippecanoe would be a great addition to your nix packages. I've been thinking more and more about how Nix could fit into this pipeline.

Great work!

The thing being discussed is designed for cloud, so I think self managed is a better description?

https://protomaps.com/docs/cdn

Self hosting pmtiles is straightforward also, make a file available to a server that supports range requests:

https://protomaps.com/docs/pmtiles#2.-serve-your-file-locall...

It might've just been this: https://github.com/protomaps/PMTiles/tree/main/serverless/aws

There isn't a tool to do that right now. It could be a fit in either https://github.com/protomaps/go-pmtiles or https://github.com/protomaps/PMTiles/tree/main/python - the Go program is faster and more production ready at this point. I imagine if folders are working for you the quantity of tiles doesn't number into the millions, so the Python program might be sufficient.

Feel free to open an issue.

PMTiles

For the next revision of the JS decoder I'm including `fflate` as a dependency so clients can decompress gzipped tile data using JavaScript.

https://github.com/protomaps/PMTiles/blob/master/js/package....

https://libgeos.org/

    GEOS is a C/C++ library for computational geometry with a focus on algorithms used in geographic information systems (GIS) software. It implements the OGC Simple Features geometry model and provides all the spatial functions in that standard as well as many others. GEOS is a core dependency of PostGIS, QGIS, GDAL, Shapely and many others.

It has the same purpose as [libgeos](https://libgeos.org/) but is implemented in Go rather than in C/C++. The primary use case is to reduce CGO dependencies while working with Go!