What does HackerNews think of planetiler?

Flexible tool to build planet-scale vector tilesets from OpenStreetMap data fast

Language: Java

For a self-hosted vector tile stack you can have a look into https://github.com/onthegomap/planetiler I found it very easy to get started and when you know the other stacks it is also very fast to create these vector tiles even for planet-scale.

(note, that I'm not affiliated with them, but they use some source code from us for the efficient import and also contributed to GraphHopper, but this did not influence my experience ;) )

> I wonder why so many seem to be moving away from raster tiles to vector data.

The flexibility of styling. And you can easily serve customers that need different default languages. This makes maps also more accessible for countries without Latin alphabet. Also when you rotate the map (like for GPS navigation) the labels can rotate too if necessary.

Ah, that makes sense.

I'd take a look at https://github.com/onthegomap/planetiler -- I bet that fits the bill for what you need if you have the servers but need the data. :)

Checkout https://github.com/onthegomap/planetiler.

Super easy way to generate a MBTiles, which you can then serve directly, or further convert to PMTiles, which can be used to host vector tiles for client-side rendering using MapLibre (or other renderers).

Raster tiles are a lot harder because you have to generate them on the server, and that's a lot more resource intensive.

You can always start with tiles from https://openstreetmap.org Or use one of the commercial providers which offers free tiers. There are quite a few smaller providers that are not super expensive.

You can always setup your own tile server. It's not that hard and can be cheap (if you don't count your time). I recommend, checking https://github.com/onthegomap/planetiler

I built planetiler (https://github.com/onthegomap/planetiler) for this purpose. The output up to z14 is ~80gb and depending on how big of a machine you have it takes from 30 minutes up to a few hours - no DB required, just java or docker. If you are only going to z11-12, it should be quite a bit faster/smaller.

Brandon from Protomaps is also helping add pmtiles output natively to planetiler, so you won't need a conversion step afterwards!

Checkout planetiler: https://github.com/onthegomap/planetiler. A super fast way to take an OSM data dump to create vector tiles.
I would also like to throw in planetiler[0] and tileserver-gl[1] which I am happily running to serve vector tiles for some regions in Germany.

[0]: https://github.com/onthegomap/planetiler [1]: https://github.com/maptiler/tileserver-gl

Nice! I was going to point out the project I’ve been working on [1] to reduce the cost but I see you’ve already found it :-) Feel free to reach out it you run into any issues!

[1] https://github.com/onthegomap/planetiler

Looks like a nice offering. For those interested in an even more self-service style option -- check out https://github.com/onthegomap/planetiler. Spin up a high-memory spot instance on your favorite cloud provider, run a command, let it run a few hours, and now you've got a complete tileset for the planet at the cost of a couple of bucks. I'm not affiliated but I've been using it for my own project (http://www.lumathon.com/map) and I've been very happy.
This is basically exactly what we do we have created a cloud optimised tar (cotar)[1] by creating a hash index of the files inside the tar.

I work with serving tiled geospatial data [2] (Mapbox vector tiles) to our users as slippy maps where we serve millions of small (mostly <100KB) files to our users, our data only changes weekly so we precompute all the tiles and store them in a tar file in s3.

We compute a index for the tar file then use s3 range requests to serve the tiles to our users, this means we can generally fetch a tile from s3 with 2 (or 1 if the index is cached) requests to s3 (generally ~20-50ms).

To get full coverage of the world with map box vector tiles it is around 270M tiles and a ~90GB tar file which can be computed from open street map data [3]

> Though even that would only work with a subset of compression methods or no compression.

We compress the individual files as a work around, there are options for indexing a compressed (gzip) tar file but the benefits of a compressed tar vs compressed files are small for our use case

[1] https://github.com/linz/cotar (or wip rust version https://github.com/blacha/cotar-rs) [2] https://github.com/linz/basemaps or https://basemaps.linz.govt.nz [3] https://github.com/onthegomap/planetiler