pygeoapi VS go-pmtiles

If you're just looking for a WFS (geojson/data) and not WMS/raster output, you might look at PyGeoAPI. (https://pygeoapi.io/) I haven't used it, but have looked at it a bit for a potential project to export geo data as an API.

Geoserver does fill a pretty big hole in the capabilities space -- it's pretty easy to get going with a bunch of layers and style them, but ultimately they're implementing a RDBMS in xml files, and it's a big, complicated, java system that's been one of the more troublesome portions of the stack (IME).

I would also like to share https://pygeoapi.io/ which relies on the new OGC API standard to share geospatial data.

python: https://pygeoapi.io - the whole project is ogcapi stuff

This may be a good start, without having to write much code. https://pygeoapi.io/

I believe pygeoapi https://pygeoapi.io/ is what you're looking for. It implements the OGC API suite of standards, and is in active development. I haven't used it yet, but hope to pretty soon within a Django project. If you do go with it I'd love to hear what you think.

https://pygeoapi.io/ link to the project. The devs are really active and helpful in Gitter of you ever have any issues

In order to publish the dataset using the OGC API Features standard, we need a software which implements the standard. In this tutorial we will use pygeoapi, which is a python server implementation, released under a FOSS (MIT) license. pygeoapi needs a backend to store the data. For that we will use the MongoDB document oriented database. In order to make deployment easier, the complete stack was virtualised into a set of docker containers, and orchestrated using docker-compose.

I just used their pmtiles tool to grab a map of just the area around Half Moon Bay, south of San Francisco.

I grabbed the latest macOS Go binary from https://github.com/protomaps/go-pmtiles/releases

I found a rough bounding box using http://bboxfinder.com/#37.373977,-122.593346,37.570977,-122....

Then I ran this:

    pmtiles extract https://build.protomaps.com/20231023.pmtiles hmb.pmtiles \

Yes, PMTiles is a tradeoff that isn't appropriate for transactional use cases. SQLite is pretty good for that already.

There is a throughput limit on S3 files of approximately 5500 GETs/sec per key. Bare archives on S3 is an appropriate choice for small-scale, zero maintenance deployments. If your application demands any thing close to that level of throughput, you're probably either:

* Serving individual tiles over the internet: you should use the CDN integration http://protomaps.com/docs/cdn ; most tile requests will be cached and only misses will interact with the S3 bottleneck.

* Bulk accessing a spatial subset of tiles: You shouldn't be requesting HTTP GETs for single tiles, but instead entire subsets of tiles with a single Range request made possible by the internal Hilbert curve ordering. This is still WIP here: https://github.com/protomaps/go-pmtiles/issues/31